[
  {
    "question": "What is the theme of the artwork in the NVIDIA Studio October 12 blog post?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTAvMTIvaW4tdGhlLW52aWRpYS1zdHVkaW8tb2N0b2Jlci0xMi8=.pdf",
    "ground_truth_answer": "The theme of the artwork in the NVIDIA Studio October 12 blog post is 'From 2D to 3D'.",
    "ground_truth_context": "\"\nCredit: @juliestrator pic.twitter.com/RsY6nLg8pT\n\n\u2014 NVIDIA Studio (@NVIDIAStudio) October 3, 2022\n\nEntering is quick and easy. Simply post a 2D piece of art next to a 3D rendition of it on Instagram , Twitter or Facebook . And be sure to tag #From2Dto3D to enter.\n\nGet creativity-inspiring updates directly to your inbox by subscribing to the NVIDIA Studio newsletter .\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/10/12/in-the-nvidia-studio-october-12/\""
  },
  {
    "question": "What is Blu Cocoon's approach to managing containers in shipyards?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDYvMjgvYS1mb29kLWluZHVzdHJ5LWJsdS1jb2Nvb24v.pdf",
    "ground_truth_answer": "Blu Cocoon is extending its work in the food supply chain into managing containers in shipyards by using computer vision models to optimize movement of containers, reducing their time in the yard and minimizing touch points to save time and money.",
    "ground_truth_context": "\"\n\u201cAs a result, we\u2019re expanding our license with Blu Cocoon to bring AI-powered insights into every area of our business,\u201d he said.\n\nInitially, the startup used CPUs to train and run its AI models. Now it exclusively uses NVIDIA GPUs and the Metropolis framework for computer vision.\n\n\u201cIt used to take us two months to train a single AI model on CPUs,\u201d said Indraganti. \u201cNow, with NVIDIA A10 Tensor Core GPUs , all four models in AGRi360 can be trained in a few hours \u2014 that\u2019s a game changer.\u201d\n\nThe time savings add up quickly because the models need to be retrained for new crops, variants and soil types.\n\nGPUs reduced the time to complete inference jobs, too. Predictions that require 15-20 minutes on CPUs get generated in 2-3 seconds on NVIDIA T4 Tensor Core GPUs . The speed also enables Blu Cocoon to test its models on large and growing datasets.\n\nLooking ahead, Blu Cocoon is extending its work in the food supply chain into managing containers in shipyards. It\u2019s already testing computer vision models for a customer in India.\n\n\u201cWe\u2019ve figured out a way to optimize movement of containers, reducing their time in the yard and minimizing touch points to save time and money,\u201d said Indraganti.\n\nThe startup is even helping food producers create recipes with AI. It\u2019s already cooked up a gluten-free muffin for one packaged-foods client with plant-based cheeses, shakes and snack bars next on the menu.\n\nOne customer reports the AI-powered system helped reduce the time to create a new recipe by 80%.\n\n\u201cWe named the company Blu Cocoon Digital because we look beyond the horizon and across the ocean for ways to nurture our customers\u2019 aspirations with digital technology \u2014 and it all runs on the NVIDIA platform and Microsoft Azure,\u201d he said.\n\nRead about Monarch Tractor to learn other ways AI is advancing agriculture.\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/06/28/a-food-industry-blu-cocoon/\""
  },
  {
    "question": "How does confidential computing protect data?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDMvMDEvd2hhdC1pcy1jb25maWRlbnRpYWwtY29tcHV0aW5nLw==.pdf",
    "ground_truth_answer": "Confidential computing protects data by isolating it from the rest of the system and encrypting it. It also provides attestation, which proves to the user that no one has tampered with the data or software. This ensures that sensitive data and intellectual property remain secure.",
    "ground_truth_context": "\"\nConfidential computing is \u201clike attaching a contract to your data that only allows certain things to be done with it,\u201d he said.\n\nTaking a deeper look, confidential computing sits on a foundation called a root of trust, which is based on a secured key unique to each processor.\n\nThe processor checks it has the right firmware to start operating with what\u2019s called a secure, measured boot. That process spawns reference data, verifying the chip is in a known safe state to start work.\n\nNext, the processor establishes a secure enclave or trusted execution environment (TEE) sealed off from the rest of the system where the user\u2019s application runs. The app brings encrypted data into the TEE, decrypts it, runs the user\u2019s program, encrypts the result and sends it off.\n\nAt no time could the machine owner view the user\u2019s code or data.\n\nOne other piece is crucial: It proves to the user no one could tamper with the data or software.\n\nThe proof is delivered through a multi-step process called attestation (see diagram above).\n\nThe good news is researchers and commercially available services have demonstrated confidential computing works, often providing data security without significantly impacting performance.\n\nAs a result, users no longer need to trust all the software and systems administrators in separate cloud and edge companies at remote locations.\n\nConfidential computing closes many doors hackers like to use. It isolates programs and their data from attacks that could come from firmware, operating systems, hypervisors, virtual machines \u2014 even physical interfaces like a USB port or PCI Express connector on the computer.\n\nThe new level of security promises to reduce data breaches that rose from 662 in 2010 to more than 1,000 by 2021 in the U.S. alone, according to a report from the Identity Theft Resource Center .\n\nThat said, no security measure is a panacea, but confidential computing is a great security tool, placing control directly in the hands of \u201cdata owners\u201d.\n\nUsers with sensitive datasets and regulated industries like banks, healthcare providers and governments are among the first to use confidential computing. But that\u2019s just the start.\n\nBecause it protects sensitive data and intellectual property, confidential computing will let groups feel they can collaborate safely. They share an attested proof their content and code was secured.\n\nExample applications for confidential computing include:\n\nCompanies executing smart contracts with blockchains\n\nResearch hospitals collaborating to train AI models that analyze trends in patient data\n\nRetailers, telecom providers and others at the network\u2019s edge, protecting personal information in locations where physical access to the computer is possible\n\nSoftware vendors can distribute products which include AI models and proprietary algorithms while preserving their intellectual property\n\nWhile confidential computing is getting its start in public cloud services, it will spread rapidly.\""
  },
  {
    "question": "What is the name of the AI-driven avatar created by NVIDIA's CEO?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTIvMjIvdG95LWplbnNlbi1qaW5nbGUtYmVsbHMv.pdf",
    "ground_truth_answer": "Toy Jensen",
    "ground_truth_context": "\"\nToy Jensen Rings in Holidays With AI-Powered \u2018Jingle Bells\u2019 As the holidays approach and the world is filled with joy and wonder, Toy Jensen, the entirely AI-driven avatar of NVIDIA\u2019s CEO, brings a song to lift people\u2019s spirits even higher.\n\nAuthor: Brian Caulfield\n\nIn a moment of pure serendipity, Lah Yileh Lee and Xinting Lee, a pair of talented singers who often stream their performances online, found themselves performing in a public square in Taipei when NVIDIA founder and CEO Jensen Huang happened upon them.\n\nHuang couldn\u2019t resist joining in, cheering on their serenade as they recorded Lady Gaga\u2019s \u201cAlways Remember Us This Way.\u201d\n\nThe resulting video quickly went viral, as did a follow-up video from the pair, who sang Lady Gaga\u2019s \u201cHold My Hand,\u201d the song Huang originally requested.\n\nNow, with the help of his AI-driven avatar, Toy Jensen, Huang has come up with a playful holiday-themed response.\n\nNVIDIA\u2019s creative team quickly developed a holiday performance by TJ, a tech demo showcasing core technologies that are part of the NVIDIA Omniverse Avatar Cloud Engine , or ACE, platform.\n\nOmniverse ACE is a collection of cloud-native AI microservices and workflows for developers to easily build, customize and deploy engaging and interactive avatars.\n\nUnlike current avatar development, which requires expertise, specialized equipment, and manually intensive workflows, Omniverse ACE is built on top of the Omniverse platform and NVIDIA\u2019s Unified Compute Framework , or UCF, which makes it possible to quickly create and configure AI pipelines with minimal coding.\n\n\u201cIt\u2019s a really amazing technology, and the fact that we can do this is phenomenal,\u201d said Cyrus Hogg, an NVIDIA technical program manager.\n\nTo make it happen, NVIDIA\u2019s team used a recently developed voice conversion model to extract the voice of a professional singer from a sample provided by them and turn it into TJ\u2019s voice \u2013 originally developed by training on hours of real world recordings. They used the musical notes from that sample and applied them to the digital voice of TJ to make the avatar sing the same notes and with the same rhythm as the original singer.\n\nThen the team used NVIDIA Omniverse ACE along with Omniverse Audio2Face and Audio2Gesture technologies to generate realistic facial expressions and body movements for the animated performance based on TJ\u2019s audio alone.\n\nWhile the team behind Omniverse ACE technologies spent years developing and fine-tuning the technology showcased in the performance, turning the music track they created into a polished video took just hours.\n\nThat gave them plenty of time to ensure an amazing performance.\n\nThey even collaborated with Jochem van der Saag , a composer and producer who has worked with Michael Bubl\u00e9 and David Foster, to create the perfect backing track for TJ to sing along to.\""
  },
  {
    "question": "What is the name of the open-source framework developed by NVIDIA for 3D graphics and compute tasks?",
    "document": "TlZJRElBIGFuZCBQYXJ0bmVycyBVU0QgOC85LzIyLnBkZg==.pdf",
    "ground_truth_answer": "The open-source framework developed by NVIDIA for 3D graphics and compute tasks is called USD (Universal Scene Description).",
    "ground_truth_context": "\"\nCertain statements in this press release including, but not limited to, statements as to: the multi-year roadmap to expand USD\u2019s capabilities beyond visual effects; our collaborations with third parties; the impact of evolving USD; international character support allowing users from all countries and languages to participate in USD; support for geospatial coordinates enabling city-scale and planetary-scale digital twins; real-time streaming of IoT data enabling the development of digital twins that are synchronized to the physical world; the rapidly growing momentum of USD as an open-source framework across VFX, animation, industrial, design and scientific applications; the benefits, performance and impact of our products and technologies, including Omniverse; the future of design, engineering and collaboration occurring in the industrial metaverse; and the promise of USD are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing product and technologies; market acceptance of our products or our partners\u2019 products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the company\u2019s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.\n\n\u00a9 2022 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo and NVIDIA Omniverse are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated.\n\nKasia Johnston +1-415-813-8859 kasiaj@nvidia.com\""
  },
  {
    "question": "Which games will be available on GeForce NOW with RTX 4080-class servers?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDgvMjIvZ2FtZXNjb20tZGxzcy1yYXktcmVjb25zdHJ1Y3Rpb24v.pdf",
    "ground_truth_answer": "Alan Wake 2, Cyberpunk 2077: Phantom Liberty DLC, PAYDAY 3, and Party Animals will be available on GeForce NOW with RTX 4080-class servers at launch.",
    "ground_truth_context": "\"\nIn addition, Call of Duty: Modern Warfare III , PAYDAY 3 , Alan Wake 2 , Cyberpunk 2077: Phantom Liberty and more will launch with NVIDIA Reflex , which reduces system latency so gamers\u2019 actions\n\noccur quicker, providing a competitive edge in multiplayer matches and making single-player titles more responsive and enjoyable.\n\nAnd Reflex is already increasing gamers\u2019 competitiveness in the latest editions of wildly popular franchises, with APEX Legends Season 18 and Overwatch 2 Invasion .\n\nNVIDIA Reflex is now used by over 50 million players each month. It\u2019s available in 9 of the top 10 competitive shooters, including the Counter-Strike 2 beta, and is activated by 90% of GeForce gamers in over 70 supported titles.\n\nHalf-Life 2 RTX: An RTX Remix Project is an in-development community remaster of one of the highest-rated games of all time , Valve\u2019s Half-Life 2 . Being developed by four of Half-Life 2 \u2019s top mod teams using RTX Remix , Half-Life 2 RTX will feature full ray tracing, DLSS 3, Reflex and RTX IO.\n\nBringing more AI to gaming, NVIDIA Avatar Cloud Engine (ACE) introduces NeMo SteerLM. This new training technique enables developers to customize the personality of NPCs for more emotive, realistic, and memorable interactions.\n\nACE is a custom AI model foundry that aims to bring intelligence to NPCs through AI-powered natural language interactions.\n\nGeForce NOW also gets new games as Ultimate members connect to more powerful servers.\n\nNVIDIA announced GeForce RTX 4080 SuperPODs are now fully deployed throughout North America and Europe, bringing exclusive access to RTX 4080-class servers to Ultimate members.\n\nThose servers will be kept plenty busy.\n\nComing soon, GeForce NOW members can stream AAA titles Alan Wake 2 , Cyberpunk 2077: Phantom Liberty DLC , PAYDAY 3 and Party Animals at launch from the cloud gaming service.\n\nAs part of NVIDIA and Microsoft\u2019s collaboration to bring more choice to gamers, Microsoft Store integration will be added to GeForce NOW in the coming days.\n\nMembers will soon be able to stream over ten supported Xbox PC Game Pass titles at GeForce RTX 4080 quality across devices of their choice. More games from Xbox\u2019s PC Game Pass library will be added to GeForce NOW on a regular basis.\n\nHead to the cloud and stream new titles joining later this week, including DOOM 2016 from Bethesda .\n\nDLSS 3.5 is being demonstrated in NVIDIA\u2019s booth (hall 2.1, booth A10) at Gamescom in Cologne, Germany, August 23-27.\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/08/22/gamescom-dlss-ray-reconstruction/\""
  },
  {
    "question": "Who are Mozhgan Kabiri Chimeh and Misbah Mubarak?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDMvMjcvZGl2ZXJzaXR5LWluLXN1cGVyY29tcHV0aW5nLw==.pdf",
    "ground_truth_answer": "Mozhgan Kabiri Chimeh and Misbah Mubarak are NVIDIANs who work in different areas of the company and on opposite sides of the Atlantic. They have collaborated closely for years, organizing biannual workshops for women in supercomputing.",
    "ground_truth_context": "\"\nTwo NVIDIANs Supercharging Diversity in Supercomputing From Opposite Sides of the Ocean\n\nAuthor: Isha Salian\n\nNVIDIANs Mozhgan Kabiri Chimeh and Misbah Mubarak work in different areas of the company \u2014 and on opposite sides of the Atlantic \u2014 but have collaborated closely for years, organizing biannual workshops for women in supercomputing.\n\nThe workshops, which take place at the annual SC and ISC annual supercomputing conferences, are hosted by Women in High Performance Computing (WHPC), an international organization that aims to improve diversity, equity and inclusion in the field.\n\nThe pair, both with Ph.D.s in computer science, grew up in Iran and Pakistan, respectively. They met through WHPC and have led the workshop committee since 2018.\n\nPictured at top: Mubarak and Kabiri Chimeh on the SC18 show floor.\n\n\u201cWe were motivated to get involved with WHPC to raise awareness of the very real challenges that women and underrepresented communities face in the workplace,\u201d said Mubarak, a New York-based principal software architect on the NVIDIA Omniverse infrastructure team. \u201cYou\u2019ll find plenty of technical workshops at the supercomputing conferences, so we work to cover topics around diversity and inclusion, such as impostor syndrome, mentorship, allyship and more.\u201d\n\n\u201cWe feel that by sharing our stories, and by bringing in diverse leaders to share their experiences, we can help give a voice to people who never had the opportunity to study or enter the field of HPC,\u201d said Kabiri Chimeh, a U.K.-based developer advocate who leads GPU bootcamps and hackathons.\n\nAs co-chairs of the WHPC workshop committee, the two collaborate with volunteers from national labs, academia and industry. The workshops they organize \u2014 typically half-day events at ISC and a full day at SC \u2014 attract dozens of participants from around the world. To help support attendees from emerging areas such as Africa and Latin America, WHPC provides free conference passes.\n\nEach event features a keynote talk, a series of sessions by women in HPC and allies, lightning talks by early-career women and a panel discussion on key challenges that underrepresented communities in HPC face.\n\nIn the past few years, the workshop committee has placed a greater focus on increasing the presence of male allies at WHPC events.\n\n\u201cEarlier, when I\u2019d ask male colleagues to attend, they\u2019d think the event was just for women in HPC,\u201d said Mubarak. \u201cBut we can make a greater impact by sharing ways allies can effectively support diverse communities at work.\u201d\n\nAt ISC22, NVIDIANs Jack Wells and CJ Newburn spoke at a WHPC session on early-career development. Wells, a scientific program manager for HPC, discussed developing an inclusive work culture. Newburn, a distinguished engineer in HPC software, presented about building character and community.\n\n\u201cThere are some great allies within NVIDIA,\u201d Kabiri Chimeh said. \u201cWe need more supporters like this to attend WHPC events and volunteer their time.\u201d\""
  },
  {
    "question": "What was the motivation behind building a mini supercomputer at SMU?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTEvMDcvc211LXRpbnktc3VwZXJjb21wdXRlci8=.pdf",
    "ground_truth_answer": "The team wanted to create a teaching tool for students to experiment with stripping wires, managing a parallel file system, reimaging cards, and deploying cluster software.",
    "ground_truth_context": "\"\nThe first iteration was a mess of wires on a table connecting the NVIDIA Jetson Nano developer kits , with cardboard boxes as heatsinks, Ozenne said.\n\n\u201cWe chose to use NVIDIA Jetson modules because no other small compute devices have onboard GPUs, which would let us tackle more AI and machine learning problems,\u201d he added.\n\nSoon Ozenne gave the baby supercomputer case upgrades: from cardboard to foam to acrylic plates, which he laser cut from 3D vector files in SMU\u2019s innovation gym, a makerspace for students.\n\n\u201cIt was my first time doing all of this, and it was a great learning experience, with lots of fun nights in the lab,\u201d Ozenne said.\n\nIn just four months, the project went from nothing to something that resembled a supercomputer, according to Ozenne. But the project is ongoing.\n\nThe team is now developing the mini cluster\u2019s software stack, with the help of the NVIDIA JetPack software development kit , and prepping it to accomplish some small-scale machine learning tasks. Plus, the baby supercomputer could level up with the recently announced NVIDIA Jetson Orin Nano modules.\n\n\u201cOur NVIDIA DGX SuperPOD just opened up on campus, so we don\u2019t really need this baby supercomputer to be an actual compute environment,\u201d Godat said. \u201cBut the mini cluster is an effective teaching tool for how all this stuff really works \u2014 it lets students experiment with stripping the wires, managing a parallel file system, reimaging cards and deploying cluster software.\u201d\n\nSMU\u2019s NVIDIA DGX SuperPOD, which includes 160 NVIDIA A100 Tensor Core GPUs , is in an alpha-rollout phase for faculty, who are using it to train AI models for molecular dynamics, computational chemistry, astrophysics, quantum mechanics and a slew of other research topics.\n\nGodat collaborates with the NVIDIA DGX team to flexibly configure the DGX SuperPOD to support tens of different AI, machine learning, data processing and HPC projects.\n\n\u201cI love it, because every day is different \u2014 I could be working on an AI-related project in the school of the arts, and the next day I\u2019m in the law school, and the next I\u2019m in the particle physics department,\u201d said Godat, who himself has a Ph.D. in theoretical particle physics from SMU.\n\n\u201cThere are applications for AI everywhere,\u201d Ozenne agreed.\n\nLearn more from Godat and other experts on designing an AI Center of Excellence in this NVIDIA GTC session available on demand .\n\nJoin NVIDIA at SC22 to explore partner booths on the show floor and engage with virtual content all week \u2014 including a special address, demos and other sessions.\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/11/07/smu-tiny-supercomputer/\""
  },
  {
    "question": "What is the focus of the upcoming GTC conference?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDMvMTMvbGVhcm4tYWJvdXQtYWktZm9yLWNsaW1hdGUtc2NpZW5jZS1ndGMv.pdf",
    "ground_truth_answer": "The focus of the upcoming GTC conference is groundbreaking technologies, including AI for climate science and Earth-2.",
    "ground_truth_context": "\"\nRegister for free to attend GTC and discover how groundbreaking technologies are shaping the world. Add sessions focused on climate change and Earth-2 to your conference agenda.\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/03/13/learn-about-ai-for-climate-science-gtc/\""
  },
  {
    "question": "What is the name of the new GeForce RTX 4090 GPU?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTAvMTIvaW4tdGhlLW52aWRpYS1zdHVkaW8tb2N0b2Jlci0xMi8=.pdf",
    "ground_truth_answer": "Sorry! The provided context does not tell anything about the name of the new GeForce RTX 4090 GPU.",
    "ground_truth_context": "\"\nGeForce RTX 4090 GPU Arrives, Enabling New World-Building Possibilities for 3D Artists This Week \u2018In the NVIDIA Studio\u2019 Featured artist Pasquale Scionti created the harrowing, beautiful \u2018Old Abandoned Haunted Mansion\u2019 using Autodesk 3ds Max, Adobe Substance 3D Painter and Unreal Engine 5.\n\nAuthor: Gerardo Delgado\n\nEditor\u2019s note: This post is part of our weekly In the NVIDIA Studio series, which celebrates featured artists, offers creative tips and tricks, and demonstrates how NVIDIA Studio technology improves creative workflows. In the coming weeks, we\u2019ll deep dive on new GeForce RTX 40 Series GPU features, technologies and resources, and how they dramatically accelerate content creation.\n\nCreators can now pick up the GeForce RTX 4090 GPU , available from top add-in card providers including ASUS, Colorful, Gainward, Galaxy, GIGABYTE, INNO3D, MSI, Palit, PNY and ZOTAC, as well as from system integrators and builders worldwide.\n\nFall has arrived, and with it comes the perfect time to showcase the beautiful, harrowing video , Old Abandoned Haunted Mansion , created by 3D artist and principal lighting expert Pasquale Scionti this week In the NVIDIA Studio .\n\nArtists like Scionti can create at the speed of light with the help of RTX 40 Series GPUs alongside 110 RTX-accelerated apps, the NVIDIA Studio suite of software and dedicated Studio Drivers.\n\nThe new GeForce RTX 4090 GPU brings an extraordinary boost in performance, third-generation RT Cores, fourth-generation Tensor Cores, an eighth-generation NVIDIA Dual AV1 Encoder and 24GB of Micron G6X memory capable of reaching 1TB/s bandwidth.\n\n3D artists can now build scenes in fully ray-traced environments with accurate physics and realistic materials \u2014 all in real time, without proxies. DLSS 3 technology uses the AI-powered RTX Tensor Cores and a new Optical Flow Accelerator to generate additional frames and dramatically increase frames per second (FPS). This improves smoothness and speeds up movement in the viewport. NVIDIA is working with popular 3D apps Unity and Unreal Engine 5 to integrate DLSS 3.\n\nDLSS 3 will also benefit workflows in the NVIDIA Omniverse platform for building and connecting custom 3D pipelines. New Omniverse tools such as NVIDIA RTX Remix for modders, which was used to create Portal with RTX , will be game changers for 3D content creation.\n\nVideo and live-streaming creative workflows are also turbocharged as the new AV1 encoder delivers 40% increased efficiency, unlocking higher resolution and crisper image quality. Expect AV1 integration in OBS Studio, DaVinci Resolve and Adobe Premiere Pro (though the Voukoder plugin) later this month.\""
  },
  {
    "question": "What is the name of the upcoming survival horror game from Remedy Entertainment and Epic Games Publishing?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDgvMjQvZ2Vmb3JjZS1ub3ctdGh1cnNkYXktYXVnLTI0Lw==.pdf",
    "ground_truth_answer": "Alan Wake 2.",
    "ground_truth_context": "\"\nAnd this week only, on top of being able to win a six-month Ultimate membership and $100 Steam gift card for making it into the top three on the weekly leaderboard of the Ultimate KovaaK\u2019s challenge, those who make it into the top 10 will get a six-month PC Game Pass. Keep an eye out on GeForce NOW\u2019s Twitter and Facebook accounts for more details.\n\nTop publishers Epic Games Publishing, CD Projekt Red and Deep Silver are all bringing their blockbuster titles to GeForce NOW at launch in the fall.\n\nUncover the newest mystery in the upcoming survival horror game Alan Wake 2 , sequel to the award-winning game Alan Wake, from Remedy Entertainment and Epic Games Publishing. Survive as the best-selling horror writer Alan Wake \u2014 who\u2019s trapped in a dark dimension and trying to write his way out \u2014 or as FBI agent Saga Anderson in a life-or-death race to solve a small-town murder that quickly spirals into a nightmare.\n\nPlay through two distinct stories set in two beautiful yet terrifying worlds and see events unfold from different perspectives. The characters must take on powerful supernatural enemies and use more than just a gun to survive: light is the ultimate weapon in the fight against darkness. Members can stream the game from the cloud when it launches on Tuesday, Oct. 27.\n\nReturn as cyber-enhanced mercenary V in the upcoming spy-thriller expansion for the hit open-world action adventure Cyberpunk 2077 from CD Projekt Red. Phantom Liberty features the all-new district of Dogtown, infinitely replayable open-world activities, an exclusive skill tree and much more \u2014 including new weapons, cyberware, vehicles and gigs for players to discover. Embark on a high-stakes mission of espionage and intrigue to save the NUS President when the expansion launches in the cloud on Tuesday, Sept. 26.\n\nJoin the Payday Gang in the upcoming third installment of the PAYDAY franchise from Starbeeze Studios, Overkill Software and Deep Silver. In PAYDAY 3 , play as notorious criminals who must face off against new enemies and challenges in an action-packed, high-octane experience. Invite your friends to the four-player online co-op mode to pull off the ultimate heist when the title launches on GeForce NOW on Thursday, Sept. 21.\n\nThese games are all headed to the cloud this fall. Upgrade to an Ultimate membership today to skip the waiting lines over free members and get access to powerful NVIDIA technology, including RTX ON and DLSS 3.5 technology for AI-powered graphics and peak-performance gaming.\n\nThe next Bethesda game to heat up the cloud is DOOM 2016. Fight through hordes of demonic forces on Mars after waking up on a Union Aerospace Corporation energy-mining facility. Play as the Doom Slayer, an unnamed space marine from the DOOM franchise, and use a variety of weapons, gadgets and melee attacks in this fast-paced, first-person shooter. Plus, several online multiplayer modes are available, so members can grab some buddies to stream with.\""
  },
  {
    "question": "What is ServiceNow's partnership with NVIDIA for?",
    "document": "U2VydmljZU5vdyBOViBHZW4gQUkgNS8xNy8yMy5wZGY=.pdf",
    "ground_truth_answer": "ServiceNow has partnered with NVIDIA to build generative AI for future product capabilities and offerings.",
    "ground_truth_context": "\"\nThis press release contains \u201cforward\u2011looking statements\u201d about the expectations, beliefs, plans, and intentions relating to its partnership with NVIDIA to build generative AI. Such statements include statements regarding future product capabilities and offerings and expected benefits to ServiceNow. Forward\u2011looking statements are subject to known and unknown risks and uncertainties and are based on potentially inaccurate assumptions that could cause actual results to differ materially from those expected or implied by the forward\u2011looking statements. If any such risks or uncertainties materialize or if any of the assumptions prove incorrect, ServiceNow\u2019s results could differ materially from the results expressed or implied by the forward\u2011looking statements made. ServiceNow undertakes no obligation, and does not intend, to update the forward\u2011looking statements. Factors that may cause actual results to differ materially from those in any forward\u2011looking statements include: (i) delays and unexpected difficulties and expenses in executing the partnership or delivering the product capabilities and offerings, (ii) changes in the regulatory landscape related to AI and (iii) uncertainty as to whether sales will justify the investments in the product capabilities and offerings. Further information on factors that could affect ServiceNow\u2019s financial and other results is included in the filings ServiceNow makes with the Securities and Exchange Commission from time to time.\n\n\u00a9 2023 ServiceNow, Inc. All rights reserved. ServiceNow, the ServiceNow logo, Now, and other ServiceNow marks are trademarks and/or registered trademarks of ServiceNow, Inc. in the United States and/or other countries.\n\nShannon McPhee NVIDIA Corporation +1-310-920-9642 smcphee@nvidia.com Theresa Ianni ServiceNow +1-216-544-6817 theresa.ianni@servicenow.com\""
  },
  {
    "question": "What is the name of the new technology demo created by NVIDIA?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDkvMjAvbnZpZGlhLXN0dWRpby1nZWZvcmNlLXJ0eC00MC1zZXJpZXMv.pdf",
    "ground_truth_answer": "The new technology demo created by NVIDIA is called Racer RTX.",
    "ground_truth_context": "\"\nTo make the deployment of AV1 seamless for developers, NVIDIA is making it available in the NVIDIA Video Codec SDK 12 in October. Developers can also access the NVENC AV1 directly with Microsoft Media Framework, through Google Chrome and Chromium, as well as in FFMPEG.\n\nBenefits to livestreamers go beyond AV1 encoding on GeForce RTX 40 Series GPUs. The SDKs that power NVIDIA Broadcast are available to developers , enabling native feature support for Logitech, Corsair and Elgato devices, or advanced workflows in OBS and Notch software. At GTC, NVIDIA updated and introduced new AI-powered effects:\n\nThe popular Virtual Background feature now includes temporal information, so random objects in the background will no longer create distractions by flashing in and out. It will be available in the next version of OBS Studio.\n\nFace Expression Estimation is a new feature that allows apps to accurately track facial expressions for face meshes, even with the simplest of webcams. It\u2019s hugely beneficial to VTubers and can be found in the next version of VTube Studio.\n\nEye Contact allows creators, like podcasters, to appear as if they\u2019re looking directly at the camera \u2014 highly useful for when the user is reading a script or looking away to engage with viewers in the chat window.\n\nTo showcase the technological advancements made possible by GeForce RTX 40 Series GPUs, a global team of NVIDIANs, led by creative director Gabriele Leone, created a stunning new technology demo, Racer RTX .\n\nLeone and team set out to one-up the fully playable, physics-based Marbles at Night RTX demo. With improved GPU performance and breakthrough advancements in NVIDIA Omniverse, Racer RTX lets the user explore different sandbox environments, highlighting the amazing 3D worlds that artists are now able to create.\n\nThe demo is a look into the next generation of content creation, \u201cwhere virtually everything is simulated,\u201d Leone said. \u201cSoon, there\u2019s going to be no need to bake lighting \u2014 content will be fully simulated, aided by incredibly powerful GeForce RTX 40 Series GPUs.\u201d\n\nThe Omniverse real-time editor empowered the artists on the project to create lights, design materials, rig physics, adjust elements and see updates immediately. They moved objects, added new geometry, changed surface types and tweaked physics.\n\nIn a traditional rasterized workflow, levels and lighting need to be baked. And in a typical art environment, only one person can work on a level at a time, leading to painstaking iteration that greatly slows the creation process. These challenges were overcome with Omniverse.\n\nAnimating behavior is also a complex and manual process for creators. Using NVIDIA MDL-based materials, Leone turned on PhysX in Omniverse, and each surface and object was automatically textured and modeled to behave as it would in real life. Ram a baseball, for example, and it\u2019ll roll away and interact with other objects until it runs out of momentum.\""
  },
  {
    "question": "How many preorders have been reported for the G6?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDcvMDUveHBlbmctZzYtY291cGUtc3V2LWRyaXZlLW9yaW4v.pdf",
    "ground_truth_answer": "Over 35,000 preorders have been reported for the G6.",
    "ground_truth_context": "\"\nBased on the more than 35,000 preorders reported for the G6 after its reveal at Auto Shanghai earlier this year, drivers are eager to get moving in this latest offering from XPENG\u2019s software-defined fleet.\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/07/05/xpeng-g6-coupe-suv-drive-orin/\""
  },
  {
    "question": "How can enterprises keep up with a constantly changing landscape across inventory, services, and more?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDMvMjEvbmVtby1sYXJnZS1sYW5ndWFnZS1tb2RlbHMtZW50ZXJwcmlzZS1kYXRhLw==.pdf",
    "ground_truth_answer": "By using the NVIDIA NeMo service to customize large language models with regularly updated, domain-specific knowledge for their applications.",
    "ground_truth_context": "\"\nMind the Gap: Large Language Models Get Smarter With Enterprise Data\n\nNVIDIA NeMo service to help enterprises combine LLMs with their proprietary data to improve chatbots, customer service and more.\n\nAuthor: Erik Pounds\n\nLarge language models available today are incredibly knowledgeable, but act like time capsules \u2014 the information they capture is limited to the data available when they were first trained. If trained a year ago, for example, an LLM powering an enterprise\u2019s AI chatbot won\u2019t know about the latest products and services at the business.\n\nWith the NVIDIA NeMo service, part of the newly announced NVIDIA AI Foundations family of cloud services, enterprises can close the gap by augmenting their LLMs with proprietary data, enabling them to frequently update a model\u2019s knowledge base without having to further train it \u2014 or start from scratch.\n\nThis new functionality in the NeMo service enables large language models to retrieve accurate information from proprietary data sources and generate conversational, human-like answers to user queries. With this capability, enterprises can use NeMo to customize large language models with regularly updated, domain-specific knowledge for their applications.\n\nThis can help enterprises keep up with a constantly changing landscape across inventory, services and more, unlocking capabilities such as highly accurate AI chatbots, enterprise search engines and market intelligence tools.\n\nNeMo includes the ability to cite sources for the language model\u2019s responses, increasing user trust in the output. Developers using NeMo can also set up guardrails to define the AI\u2019s area of expertise, providing better control over the generated responses.\n\nQuantiphi \u2014 an AI-first digital engineering solutions and platforms company and one of NVIDIA\u2019s service delivery partners \u2014 is working with NeMo to build a modular generative AI solution called baioniq that will help enterprises build customized LLMs to boost worker productivity. Its developer teams are creating tools that let users search up-to-date information across unstructured text, images and tables in seconds.\n\nAnalysts estimate that around two-thirds of enterprise data is untapped. This so-called dark data is unused partly because it\u2019s difficult to glean meaningful insights from vast troves of information. Now, with NeMo, businesses can retrieve insights from this data using natural language queries.\n\nNeMo can help enterprises build models that can learn from and react to an evolving knowledge base \u2014 independent of the dataset that the model was originally trained on. Rather than needing to retrain an LLM to account for new information, NeMo can tap enterprise data sources for up-to-date details. Additional information can be added to expand the model\u2019s knowledge base without modifying its core capabilities of language processing and text generation.\""
  },
  {
    "question": "What is the goal of Relation Therapeutics' research?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDUvMTgvY2FtYnJpZGdlLTEtYWktc3VwZXJjb21wdXRlci1leHBhbmRzLXZpYS1kZ3gtY2xvdWQv.pdf",
    "ground_truth_answer": "The goal of Relation Therapeutics' research is to better understand how genes are controlled in certain diseases, which is a key step to creating new medicines.",
    "ground_truth_context": "\"\nRelation Therapeutics developed a large language model which reads DNA to better understand genes, which is a key step to creating new medicines. Their research takes us a step closer to understanding how genes are controlled in certain diseases.\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/05/18/cambridge-1-ai-supercomputer-expands-via-dgx-cloud/\""
  },
  {
    "question": "What is the name of the conversational AI platform developed by Minerva CQ?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTEvMjEvbWluZXJ2YWNxLw==.pdf",
    "ground_truth_answer": "The conversational AI platform developed by Minerva CQ is named Riva.",
    "ground_truth_context": "\"\n\u201cRiva is also fully customizable to solve our customers\u2019 unique problems and comes with industry-leading out-of-the-box accuracy,\u201d said Daniel Hong, chief marketing officer at Minerva CQ. \u201cWe were able to quickly and efficiently fine-tune the pretrained language models with help from experts on the NVIDIA Riva team.\u201d\n\nAccess to technical experts is one benefit of being part of NVIDIA Inception, a free, global program that nurtures cutting-edge startups. Spera listed AWS credits, support on experimental projects, and collaboration on go-to-market strategy among the ways Inception has bolstered Minerva CQ.\n\nIn addition to Riva, Minerva CQ uses the NVIDIA NeMo framework to build and train its conversational AI models, as well as the NVIDIA Triton Inference Server to deliver fast, scalable AI model deployment.\n\nComplementing its focus on the customer, Minerva CQ is also dedicated to agent wellness and building capabilities to track agent satisfaction and experience. The platform enables employees to be experts at their jobs from day one \u2014 which greatly reduces stress on agents, instills confidence, and lowers attrition rates and operational costs.\n\nPlus, Minerva CQ automatically provides summary reports of conversations, giving agents and supervisors helpful feedback, and analytics teams powerful business insights.\n\n\u201cAll in all, Minerva CQ empowers agents with knowledge and allows them to be confident in the information they share with customers,\u201d Hong said. \u201cEasy customer inquiries can be tackled by automated self-service or AI chatbots, so when the agents are hit with complex questions, Minerva can help.\u201d\n\nMinerva CQ\u2019s initial deployments are focused on retail energy and electrification.\n\nFor retail energy providers, the platform offers agents simple, consistent explanations of energy sources, tariff plans, billing changes and optimal spending choices.\n\nIt also assists agents to resolve complex problems for electric vehicle customers, and helps EV technicians troubleshoot infrastructure and logistics issues.\n\n\u201cRetail energy and electrification are inherently intertwined in the movement toward decarbonization, but they can still be relatively siloed in the market space,\u201d Garrett said. \u201cMinerva helps bring them together.\u201d\n\nMinerva CQ is deployed by a leading electric mobility company as well as one of the largest utilities in the world, according to Spera.\n\nThese clients\u2019 contact centers across the U.S. and Mexico have seen a 40% decrease in average handle time for a customer service call thanks to Minerva CQ, Spera said. Deployment is planned to expand further into the Spanish-speaking market \u2014 as well as in countries where Italian is spoken.\n\n\u201cWe all want to save the planet, but it\u2019s important that change come from the bottom up by empowering end users to make steps toward decarbonization,\u201d Spera said. \u201cOur focus is on providing customers with information so they can best transition to clean-energy-source subscriptions.\u201d\""
  },
  {
    "question": "How can generative AI be used in vehicle design?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDgvMDkvZ2VuZXJhdGl2ZS1haS1hdXRvLWluZHVzdHJ5Lw==.pdf",
    "ground_truth_answer": "Generative AI can be used to instantly transform 2D sketches into NURBS models, assisting designers in exploring a wide range of options faster. It can also be used to generate design elements such as textures and patterns, and to create 3D models of interior design elements such as seats and dashboards.",
    "ground_truth_context": "\"\nThe process involves looking at vehicles across the industry, whether existing or historic. Then, with a great deal of human curation, some blend of popular designs and fresh inspirations based on a company\u2019s stylings emerge. That forms the basis for artists\u2019 2D hand-drawn sketches that are then recreated as 3D models and clay prototypes.\n\nThese linear and time-consuming design concept processes are utilized for exterior parts like grilles, hoods and wheels, as well as interior aspects such as dashboards, seats, ergonomics and user interfaces.\n\nTo develop these 3D models, automotive styling teams work with engineers in tools like Autodesk Alias or Maya to develop \u201cNURBS\u201d models, short for non-uniform rational B-splines. The resulting mathematical representations of 3D geometry capture the shapes from 2D drafts. The end deliverable is a 3D representation that\u2019s the result of bespoke styling, design and engineering work and can be used in computer-aided design applications to define surfaces.\n\nThe automotive industry now has an opportunity to use generative AI to instantly transform 2D sketches into NURBS models for leaps in productivity. These tools will not replace designers, but enable them to explore a wide range of options faster.\n\nDesign-oriented enterprises can use visual datasets and generative AI to assist their work across many fronts. This has already been achieved with coding tools such as GitHub Copilot \u2014 trained on billions of lines of code \u2014 and similarly promises to help compress lengthy design timelines.\n\nIn particular, when looking for \u201cscrap\u201d design elements, generative AI models can be trained on an automaker\u2019s portfolio as well as vehicles industrywide, assisting this workflow. This can happen first by fine-tuning a small dataset of images with transfer learning , and then by tapping into NVIDIA TAO Toolkit . Or it might require a more robust dataset of some 100 million images, depending on the requirements of the generative AI model.\n\nIn this bring-your-own-model setup, design teams and developers could harness NVIDIA Picasso \u2014 a cloud-based foundry for building generative AI models for visual design \u2014 with Stable Diffusion .\n\nIn this case, designers and artists prompt the generative AI for design elements, such as \u201crugged,\u201d \u201csophisticated\u201d or \u201csleek.\u201d It then generates examples from the external world of automakers as well as from a company\u2019s internal catalogs of images, vastly accelerating this initial phase.\n\nFor vehicle interiors, large language models for text-to-image generation can enable designers to type in a description of a texture, like a floral pattern, and the generative AI will put it onto the surface of a seat, door panel or dashboard. If a designer wants to use a particular image to generate an interior design texture, generative AI can handle image-to-image texture creation.\""
  },
  {
    "question": "What is the name of the first NVIDIA-Certified System from Cisco that is compatible with NVIDIA AI Enterprise?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDEvMTkvYWktZW50ZXJwcmlzZS1yZWxlYXNlLw==.pdf",
    "ground_truth_answer": "Cisco UCS C240 M6 rack server",
    "ground_truth_context": "\"\n\u201cAI is a very popular modern workload that is increasingly favoring deployment in containers. However, deploying AI capabilities at scale within the enterprise can be extremely complex, requiring enablement at multiple layers of the stack, from AI software frameworks, operating systems, containers, VMs, and down to the hardware,\u201d said Gary Chen, research director, Software Defined Compute at IDC. \u201cTurnkey, full-stack AI solutions can greatly simplify deployment and make AI more accessible within the enterprise.\u201d\n\nThe 1.1 release of NVIDIA AI Enterprise also provides validation for the Domino Data Lab Enterprise MLOps Platform with VMware vSphere with Tanzu. This new integration enables more companies to cost-effectively scale data science by accelerating research, model development, and model deployment on mainstream accelerated servers.\n\n\u201cThis new phase of our collaboration with NVIDIA further enables enterprises to solve the world\u2019s most challenging problems by putting models at the heart of their businesses,\u201d said Thomas Robinson, vice president of Strategic Partnerships at Domino Data Lab. \u201cTogether, we are providing every company the end-to-end platform to rapidly and cost-effectively deploy models enterprise-wide.\u201d\n\nAmidst the new release of NVIDIA AI Enterprise, the industry ecosystem is expanding with the first NVIDIA-Certified Systems from Cisco and Hitachi Vantara, as well as a growing roster of newly qualified system integrators offering solutions for the software suite.\n\nThe first Cisco system to be NVIDIA-Certified for NVIDIA AI Enterprise is the Cisco UCS C240 M6 rack server with NVIDIA A100 Tensor Core GPUs . The two-socket, 2RU form factor can power a wide range of storage and I/O-intensive applications, such as big data analytics, databases, collaboration, virtualization, consolidation and high-performance computing.\n\n\u201cAt Cisco we are helping simplify customers\u2019 hybrid cloud and cloud-native transformation. NVIDIA-Certified Cisco UCS servers, powered by Cisco Intersight, deliver the best-in-class AI workload experiences in the market,\u201d said Siva Sivakumar, vice president of product management at Cisco. \u201cThe certification of the Cisco UCS C240 M6 rack server for NVIDIA AI Enterprise allows customers to add AI using the same infrastructure and management software deployed throughout their data center.\u201d\n\nThe first NVIDIA-Certified System from Hitachi Vantara compatible with NVIDIA AI Enterprise is the Hitachi Advanced Server DS220 G2 with NVIDIA A100 Tensor Core GPUs. The general-purpose, dual-processor server is optimized for performance and capacity, and delivers a balance of compute and storage with the flexibility to power a wide range of solutions and applications.\""
  },
  {
    "question": "How can NeMo-powered internal search engines help employees retrieve information within an enterprise?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDMvMjEvbmVtby1sYXJnZS1sYW5ndWFnZS1tb2RlbHMtZW50ZXJwcmlzZS1kYXRhLw==.pdf",
    "ground_truth_answer": "NeMo-powered internal search engines can help employees retrieve information faster and more easily by providing precise, up-to-date information from a wealth of knowledge across the organization, including technical documentation, company policies, and IT support articles.",
    "ground_truth_context": "\"\nEnterprises can also use NeMo to build guardrails so that generative AI applications don\u2019t provide opinions on topics outside their defined area of expertise.\n\nBy customizing an LLM with business data, enterprises can make their AI applications agile and responsive to new developments.\n\nChatbots: Many enterprises already use AI chatbots to power basic customer interactions on their websites. With NeMo, companies could build virtual subject-matter experts specific to their domains.\n\nCustomer service: Companies could update NeMo models with details about their latest products, helping live service representatives more easily answer customer questions with precise, up-to-date information.\n\nEnterprise search: Businesses have a wealth of knowledge across the organization, including technical documentation, company policies and IT support articles. Employees could query a NeMo-powered internal search engine to retrieve information faster and more easily.\n\nMarket intelligence: The financial industry collects insights about global markets, public companies and economic trends. By connecting an LLM to a regularly updated database, investors and other experts could quickly identify useful details from a large set of information, such as regulatory documents, recordings of earnings calls or financial statements.\n\nEnterprises interested in adding generative AI capabilities to their applications can apply for early access to the NeMo service.\n\nWatch NVIDIA founder and CEO Jensen Huang discuss NVIDIA AI Foundations in the keynote address at NVIDIA GTC , running online through Thursday, March 23:\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/03/21/nemo-large-language-models-enterprise-data/\""
  },
  {
    "question": "What is the estimated price of the new NVIDIA RTX 4000 SFF GPU?",
    "document": "TlZJRElBIFJlZGVmaW5lcyBXb3Jrc3RhdGlvbnMgMy8yMS8yMy5wZGY=.pdf",
    "ground_truth_answer": "The estimated price of the new NVIDIA RTX 4000 SFF GPU is $1,250.",
    "ground_truth_context": "\"\nCUDA cores: Up to 2x the single-precision floating point throughput of the previous generation. Third-generation RT Cores: Up to 2x the throughput of the previous generation, with the ability to concurrently run ray tracing with either shading or denoising capabilities. Fourth-generation Tensor Cores: Up to 2x faster AI training performance of the previous generation, with expanded support for the FP8 data format. DLSS 3: New levels of realism and interactivity for real-time graphics by multiplying performance with AI. Greater GPU memory:\n\nThe RTX 4000 SFF provides 20GB of memory with greater bandwidth than the previous generation. The GPU can transfer data to and from its memory more quickly, resulting in improved graphics, compute and rendering performance. The new NVIDIA RTX Ada Generation Laptop GPUs provide up to 16GB of graphics memory to handle the largest models, scenes, assemblies and advanced multi-application workflows.\n\nExtended-reality capabilities: The RTX 4000 SFF and new NVIDIA RTX laptop GPUs provide support for high- resolution augmented-reality and virtual-reality devices, and deliver the high-performance graphics required for experiencing stunning AR, VR and mixed-reality content.\n\nAvailability Next-generation desktop workstations featuring NVIDIA RTX GPUs will be available starting this month from global workstation manufacturing partners including BOXX, HP Inc. and Lenovo.\n\nThe new NVIDIA RTX laptop GPUs will be available starting this month in mobile workstations from global workstation manufacturer partners. The new NVIDIA RTX 4000 SFF GPU will be available from global distribution partners such as Leadtek, PNY and Ryoyo Electro starting in April at an estimated price of $1,250 and from global workstation manufacturers later this year.\n\nTo learn more about NVIDIA RTX, watch NVIDIA founder and CEO Jensen Huang\u2019s GTC 2023 keynote. Register free for GTC to attend sessions with NVIDIA and industry leaders.\n\nAbout NVIDIA Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company\u2019s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry. More information at https://nvidianews.nvidia.com/.\""
  },
  {
    "question": "What is the name of the studio that created the visual effects for Avatar: The Way of Water?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDMvMDcvb3NjYXItdmlzdWFsLWVmZmVjdHMv.pdf",
    "ground_truth_answer": "Wntn FX",
    "ground_truth_context": "\"\nReady for Its Closeup: NVIDIA Powers 15 Years of Oscar-Worthy Visual Effects\n\nAuthor: Rick Champagne\n\nThe Academy Award nominations are in \u2014 and for the 15th year in a row, NVIDIA technologies worked behind the scenes of every film nominated for Best Visual Effects.\n\nThe five VFX contenders for the 95th annual Academy Awards, taking place on Sunday, March 12, include:\n\nAll Quiet on the Western Front\n\nAvatar: The Way of Water\n\nThe Batman\n\nBlack Panther: Wakanda Forever\n\nTop Gun: Maverick\n\nFor over a decade, filmmakers and VFX studios around the world have used NVIDIA technologies to power the most advanced, visually rich movies ever made. Today, creators and artists are transforming VFX using advanced capabilities in graphics, like real-time ray tracing, simulation, AI and virtual production \u2014 all powered by NVIDIA RTX technologies. Award-winning studio Wntn FX created the stunning visuals for director James Cameron\u2019s much-anticipated sequel, Avatar: The Way of Water. The film is one of Wntn\u2019s largest VFX projects to date. The team created 3,240 shots \u2014 which is 98% of the total shots in the film, more than two-thirds of which featured water.\n\nIn computer graphics (CG), making water look natural and realistic \u2014 from how it moves off a character\u2019s skin to how it drips from clothing \u2014 is one of the biggest challenges for visual effects artists. But for this film, Wntn developed and implemented a new water toolset that advanced their capabilities across simulation, rendering and more.\n\nThe team started with pre-production and performance capture using a real-time, GPU-based ocean spectrum deformer, which served as a consistent, physically based starting point for water on set. From there, Wntn created a new suite of water solvers \u2014 many of them within Loki, the studio\u2019s in-house multiphysics simulation framework. Loki allows coupling of multiple solvers in any configuration. For example, hair, cloth, air and water can all be simulated together. Other key innovations from Wntn centered on both dry and wet performance capture, new deep learning models to process stereo camera images and generate depth maps for compositing, and neural networks to assist with facial animation and muscle systems. Wntn FX was also behind the cinematic visuals for The Batman. The team, led by VFX supervisor Anders Langlands, worked on the gripping highway chase between Batman and the infamous villain, the Penguin. As they race through the city of Gotham under heavy rainfall, the Penguin sets off a sequence of car crashes and explosions.\""
  },
  {
    "question": "How can AI help rural farmers in India?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDkvMDgvbnZpZGlhLWluZGlhLWdpYW50cy1haS8=.pdf",
    "ground_truth_answer": "AI can help rural farmers in India by providing weather information and crop prices via cell phones in their local language.",
    "ground_truth_context": "\"\nApplied in the Indian context, AI can help rural farmers interact via cell phones in their local language to get weather information and crop prices. It can help provide, at a massive scale, expert diagnosis of medical symptoms and imaging scans where doctors may not be immediately available. It can better predict cyclonic storms using decades of atmospheric data, enabling those at risk to more quickly evacuate and find shelter.\n\nReliance Industries and Tata Communications will build and operate state-of-the-art AI supercomputing data centers based on such technology, utilizing it for internal AI development and infrastructure-as-a-service for India\u2019s AI researchers, companies and burgeoning AI startup ecosystem.\n\nThat effort, Huang said, during his conversation with the Indian technology press, promises to be part of a process that will turn India into a beacon for AI technology.\n\n\u201cAI could be built in India, used in India, and exported from India,\u201d Huang said.\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/09/08/nvidia-india-giants-ai/\""
  },
  {
    "question": "What is the name of the new model developed by NVIDIA Robotics and the University of Washington for collision-free motion generation in real-time?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDYvMjkvd2hhdC1pcy1yb2JvdGljcy1zaW11bGF0aW9uLw==.pdf",
    "ground_truth_answer": "Motion Policy Networks (MpNets)",
    "ground_truth_context": "\"\nCurrently, developers can train robots for specific settings \u2014 a factory floor, fulfillment center or manufacturing plant. Within that, simulations can solve problems for specific robots, such as palette jacks, robotic arms and walking robots. Amid these chaotic setups and robot types, there are plenty of people and obstacles to avoid. In such scenes, collision-free motion generation for unknown, cluttered environments is a core component of robotics applications.\n\nTraditional motion planning approaches that attempt to address these challenges can come up short in unknown or dynamic environments. SLAM \u2014 or simultaneous localization and mapping \u2014 can be used to generate 3D maps of environments with camera images from multiple viewpoints, but it requires revisions when objects move and environments are changed.\n\nTo help overcome some of these shortcomings, the NVIDIA Robotics research team has co-developed with the University of Washington a new model , dubbed Motion Policy Networks (or MpNets) . MpNets is an end-to-end neural policy that generates collision-free motion in real time using a continuous stream of data coming from a single fixed camera. MpNets has been trained on more than 3 million motion planning problems using a pipeline of geometric fabrics from NVIDIA Omniverse and 700 million point clouds rendered in simulation. Training it on large datasets enables navigation of unknown environments in the real world. Apart from directly learning a trajectory model as in MpNets, the team also recently unveiled a new point cloud-based collision model called CabiNet . With the CabiNet model, one can deploy general purpose pick-and-place policies of unknown objects beyond a tabletop setup. CabiNet was trained with over 650,000 procedurally generated simulated scenes and was evaluated in NVIDIA Isaac Gym . Training with a large synthetic dataset allowed it to generalize to even out-of-distribution scenes in a real kitchen environment, without needing any real data.\n\nDevelopers, engineers and researchers can quickly experiment with different kinds of robot designs in virtual environments, bypassing time-consuming and expensive physical testing methods.\n\nApplying different kinds of robot designs, in combination with robot software, to test the robot\u2019s programming in a virtual environment before building out the physical machine reduces risks of having quality issues to fix afterwards.\n\nWhile this can vastly accelerate the development timeline, it can also drastically cut costs for building and testing robots and AI models while ensuring safety.\n\nAdditionally, robot simulation helps connect robots with business systems, such as inventory databases, so a robot knows where an item is located.\n\nSimulation of cobots, or robots working with humans, promises to reduce injuries and make jobs easier, enabling more efficient delivery of all kinds of products.\n\nAnd with packages arriving incredibly fast in homes everywhere, what\u2019s not to like.\""
  },
  {
    "question": "What is the significance of the partnership between NVIDIA and Foxconn?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDEvMDMvZ2FtaW5nLWNyZWF0b3Itcm9ib3RpY3MtYXV0by1jZXMv.pdf",
    "ground_truth_answer": "The partnership between NVIDIA and Foxconn will enable Foxconn to build electric vehicles based on NVIDIA DRIVE Hyperion, which will have leading electric range and state-of-the-art autonomous driving technology, while reducing time to market.",
    "ground_truth_context": "\"\n\u201cWe are committed to advancing robotics and arguably investing more than anyone else in the world,\u201d Talla said. \u201cWe are well on the way to having a thousand to million times more virtual robots for every physical robot deployed.\u201d\n\nThe NVIDIA DRIVE platform is open and easy to program, said Ali Kani, vice president of automotive at NVIDIA.\n\nHundreds of partners across the automotive ecosystem are now developing software on NVIDIA DRIVE, including 20 of the top 30 manufacturers building new energy vehicles, many of the industry\u2019s\n\ntop tier one manufacturers and software makers, plus eight of the largest 10 trucking and robotaxi companies.\n\nIt\u2019s a number that continues to grow, with Kani announcing a partnership with Foxconn , the world\u2019s largest technology manufacturer and service provider, to build electric vehicles based on NVIDIA DRIVE Hyperion .\n\n\u201cWith Hyperion adoption, Foxconn will manufacture vehicles with leading electric range as well as state-of-the-art AV technology while reducing time to market,\u201d Kani said.\n\nKani touched on how, as next-generation cars become autonomous and electric, interiors are transformed into mobile living spaces, complete with the same entertainment available at home. GeForce NOW will be \u201ccoming to screens in your car,\u201d Kani said.\n\nKani also announced several DRIVE partners are integrating GeForce NOW , including Hyundai Motor Group, BYD and Polestar.\n\nWhile gamers will enjoy virtual worlds from inside their cars, tools such as the metaverse are critical to the development and testing of new autonomous vehicles.\n\nKani announced that Mercedes-Benz is using digital twin technology to plan and build more efficient production facilities. \u201cThe applications for Omniverse in the automotive market are staggering,\u201d Kani said.\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/01/03/gaming-creator-robotics-auto-ces/\""
  },
  {
    "question": "What is the name of the game engine that will have a plug-in for NVIDIA DLSS 3?",
    "document": "TmV1cmFsIEdyYXBoaWNzIERMU1MgMyAzLzE2LzIzLnBkZg==.pdf",
    "ground_truth_answer": "Unreal Engine.",
    "ground_truth_context": "\"\n\u201cSupporting smooth gameplay in Diablo IV is a priority for Blizzard,\u201d said Michael Bukowski, Diablo IV technical director at Blizzard Entertainment. \u201cWe\u2019re excited by the high frame rate of Diablo IV running on NVIDIA GeForce RTX 40 Series hardware and DLSS 3.\u201d\n\nAdditional PC games announcing support of NVIDIA DLSS at GDC include Deceive Inc., Gripper, Smalland: Survive the Wilds and THE FINALS. View the complete list of 270 games and apps that support DLSS.\n\nDLSS Frame Generation Publicly Available for Developers at GDC NVIDIA will make DLSS Frame Generation plug-ins publicly available during GDC, allowing even more developers to integrate the framerate boosting technology into their games and applications.\n\nDLSS Frame Generation will be available to access via NVIDIA Streamline, an open-source, cross-vendor framework that simplifies the integration of super-resolution technologies in 3D games and apps.\n\nDLSS technology is always improving through ongoing training on NVIDIA\u2019s AI supercomputer. The public release will incorporate the latest DLSS enhancements made earlier this year, including:\n\nDLSS Frame Generation takes better advantage of game engine data, improving user interface stability and image quality during fast movement. DLSS Super Resolution improves Ultra Performance mode, with finer detail stability and overall better image quality. DLAA improves image quality, reduces ghosting and improves edge smoothness in high-contrast scenarios.\n\nUnreal Engine 5.2 Integration, Adding DLSS 3 to Unreal Engine Games Simpler Than Ever NVIDIA and Epic announced the integration of NVIDIA DLSS 3 into the popular Unreal Engine (UE) game engine. Unreal Engine is an open and advanced real-time 3D creation tool that gives game developers and creators the freedom and control to deliver cutting-edge real-time 3D content, interactive experiences and immersive virtual worlds. The DLSS 3 plug-in will debut in UE 5.2, making it simpler for any developer to accelerate the performance of their game or application.\n\n\u201cNVIDIA DLSS 3 introduces truly impressive frame generation technology and the Unreal Engine 5.2 plug-in will offer developers a great choice for increased quality and performance of their games,\u201d said Nick Penwarden, vice president of engineering at Epic Games.\n\nAbout NVIDIA Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company\u2019s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry. More information at https://nvidianews.nvidia.com/.\""
  },
  {
    "question": "Where can I listen to the AI Podcast?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDgvMzAvZGVlcGR1Yi8=.pdf",
    "ground_truth_answer": "You can listen to the AI Podcast on various platforms such as Amazon Music, iTunes, Google Podcasts, Google Play, Castbox, DoggCatcher, Overcast, PlayerFM, Pocket Casts, Podbay, PodBean, PodCruncher, PodKicker, Soundcloud, Spotify, Stitcher, and TuneIn.",
    "ground_truth_context": "\"\nThe AI Podcast is now available through Amazon Music .\n\nIn addition, get the AI Podcast through iTunes , Google Podcasts , Google Play , Castbox , DoggCatcher, Overcast , PlayerFM , Pocket Casts, Podbay , PodBean , PodCruncher, PodKicker, Soundcloud , Spotify , Stitcher and TuneIn .\n\nMake the AI Podcast better. Have a few minutes to spare? Fill out this listener survey .\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/08/30/deepdub/\""
  },
  {
    "question": "What is the benefit of DLSS 3 technology for 3D artists?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTAvMTIvaW4tdGhlLW52aWRpYS1zdHVkaW8tb2N0b2Jlci0xMi8=.pdf",
    "ground_truth_answer": "DLSS 3 technology uses the AI-powered RTX Tensor Cores and a new Optical Flow Accelerator to generate additional frames and dramatically increase frames per second (FPS), improving smoothness and speeding up movement in the viewport.",
    "ground_truth_context": "\"\nGeForce RTX 4090 GPU Arrives, Enabling New World-Building Possibilities for 3D Artists This Week \u2018In the NVIDIA Studio\u2019 Featured artist Pasquale Scionti created the harrowing, beautiful \u2018Old Abandoned Haunted Mansion\u2019 using Autodesk 3ds Max, Adobe Substance 3D Painter and Unreal Engine 5.\n\nAuthor: Gerardo Delgado\n\nEditor\u2019s note: This post is part of our weekly In the NVIDIA Studio series, which celebrates featured artists, offers creative tips and tricks, and demonstrates how NVIDIA Studio technology improves creative workflows. In the coming weeks, we\u2019ll deep dive on new GeForce RTX 40 Series GPU features, technologies and resources, and how they dramatically accelerate content creation.\n\nCreators can now pick up the GeForce RTX 4090 GPU , available from top add-in card providers including ASUS, Colorful, Gainward, Galaxy, GIGABYTE, INNO3D, MSI, Palit, PNY and ZOTAC, as well as from system integrators and builders worldwide.\n\nFall has arrived, and with it comes the perfect time to showcase the beautiful, harrowing video , Old Abandoned Haunted Mansion , created by 3D artist and principal lighting expert Pasquale Scionti this week In the NVIDIA Studio .\n\nArtists like Scionti can create at the speed of light with the help of RTX 40 Series GPUs alongside 110 RTX-accelerated apps, the NVIDIA Studio suite of software and dedicated Studio Drivers.\n\nThe new GeForce RTX 4090 GPU brings an extraordinary boost in performance, third-generation RT Cores, fourth-generation Tensor Cores, an eighth-generation NVIDIA Dual AV1 Encoder and 24GB of Micron G6X memory capable of reaching 1TB/s bandwidth.\n\n3D artists can now build scenes in fully ray-traced environments with accurate physics and realistic materials \u2014 all in real time, without proxies. DLSS 3 technology uses the AI-powered RTX Tensor Cores and a new Optical Flow Accelerator to generate additional frames and dramatically increase frames per second (FPS). This improves smoothness and speeds up movement in the viewport. NVIDIA is working with popular 3D apps Unity and Unreal Engine 5 to integrate DLSS 3.\n\nDLSS 3 will also benefit workflows in the NVIDIA Omniverse platform for building and connecting custom 3D pipelines. New Omniverse tools such as NVIDIA RTX Remix for modders, which was used to create Portal with RTX , will be game changers for 3D content creation.\n\nVideo and live-streaming creative workflows are also turbocharged as the new AV1 encoder delivers 40% increased efficiency, unlocking higher resolution and crisper image quality. Expect AV1 integration in OBS Studio, DaVinci Resolve and Adobe Premiere Pro (though the Voukoder plugin) later this month.\""
  },
  {
    "question": "How can I listen to the AI Podcast?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDEvMDQvdW5pdmVyc2l0eS1vZi1mbG9yaWRhLWFpLw==.pdf",
    "ground_truth_answer": "You can listen to the AI Podcast through various platforms such as Amazon Music, Apple Music, Google Podcasts, Google Play, Castbox, DoggCatcher, Overcast, PlayerFM, Pocket Casts, Podbay, PodBean, PodCruncher, PodKicker, Soundcloud, Spotify, Stitcher, and TuneIn.",
    "ground_truth_context": "\"\nYou can now listen to the AI Podcast through Amazon Music .\n\nAlso get the AI Podcast through Apple Music , Google Podcasts , Google Play , Castbox , DoggCatcher, Overcast , PlayerFM , Pocket Casts, Podbay , PodBean , PodCruncher, PodKicker, Soundcloud , Spotify , Stitcher and TuneIn .\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/01/04/university-of-florida-ai/\""
  },
  {
    "question": "What is the name of the autonomous vehicle development company featured in the article?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDkvMTQvZ2F0aWstcG9kY2FzdC8=.pdf",
    "ground_truth_answer": "The name of the autonomous vehicle development company featured in the article is Gatik.",
    "ground_truth_context": "\"\nReinventing the Wheel: Gatik\u2019s Apeksha Kumavat Accelerates Autonomous Delivery for Wal-Mart and More\n\nAuthor: Brian Caulfield\n\nAs consumers expect faster, cheaper deliveries, companies are turning to AI to rethink how they move goods.\n\nForemost among these new systems are \u201chub-and-spoke,\u201d or middle-mile, operations, where companies place distribution centers closer to retail operations for quicker access to inventory. However, faster delivery is just part of the equation. These systems must also be low-cost for consumers.\n\nAutonomous delivery company Gatik seeks to provide lasting solutions for faster and cheaper shipping. By automating the routes between the hub \u2014 the distribution center \u2014 and the spokes \u2014 retail stores \u2014 these operations can run around the clock efficiently and with minimal investment.\n\nGatik co-founder and Chief Engineer Apeksha Kumavat joined NVIDIA\u2019s Katie Burke Washabaugh on the latest episode of the AI Podcast to walk through how the company is developing autonomous trucks for middle-mile delivery.\n\nKumavat also discussed the progress of commercial pilots with companies such as Walmart and Georgia-Pacific.\n\nShe\u2019ll elaborate on Gatik\u2019s autonomous vehicle development in a virtual session at NVIDIA GTC on Tuesday, Sept. 20. Register free to learn more.\n\nDriver\u2019s Ed: How Waabi Uses AI, Simulation to Teach Autonomous Vehicles to Drive\n\nTeaching the AI brains of autonomous vehicles to understand the world as humans do requires billions of miles of driving experience. The road to achieving this astronomical level of driving leads to the virtual world. Learn how Waabi uses powerful high-fidelity simulations to train and develop production-level autonomous vehicles.\n\nPolestar\u2019s Dennis Nobelius on the Sustainable Performance Brand\u2019s Plans\n\nDriving enjoyment and autonomous driving capabilities can complement one another in intelligent, sustainable vehicles. Learn about the automaker\u2019s plans to unveil its third vehicle, the Polestar 3, the tech inside it, and what the company\u2019s racing heritage brings to the intersection of smarts and sustainability.\n\nGANTheftAuto: Harrison Kinsley on AI-Generated Gaming Environments\n\nHumans playing games against machines is nothing new, but now computers can develop their own games for people to play. Programming enthusiast and social media influencer Harrison Kinsley created GANTheftAuto, an AI-based neural network that generates a playable chunk of the classic video game, Grand Theft Auto V .\n\nThe AI Podcast is now available through Amazon Music .\n\nIn addition, get the AI Podcast through iTunes , Google Podcasts , Google Play , Castbox , DoggCatcher, Overcast , PlayerFM , Pocket Casts, Podbay , PodBean , PodCruncher, PodKicker, Soundcloud , Spotify , Stitcher and TuneIn .\n\nMake the AI Podcast better: Have a few minutes to spare? Fill out this listener survey .\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/09/14/gatik-podcast/\""
  },
  {
    "question": "What company has announced a digital twin solution for telco network planning and operations?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDkvMjAvaGVhdnktYWktZGlnaXRhbC10d2luLW9tbml2ZXJzZS8=.pdf",
    "ground_truth_answer": "HEAVY.AI has announced a digital twin solution for telco network planning and operations.",
    "ground_truth_context": "\"\nHEAVY.AI Delivers Digital Twin for Telco Network Planning and Operations Based on NVIDIA Omniverse With 5G deployments set to double through 2027, HEAVY.AI\u2019s framework built on NVIDIA Omniverse helps optimize wireless site placements to reduce the cost and complexity of network operations and improve the customer experience.\n\nAuthor: Soma Velayutham\n\nTelecoms began touting the benefits of 5G networks six years ago. Yet the race to deliver ultrafast wireless internet today resembles a contest between the tortoise and the hare, as some mobile network operators struggle with costly and complex network requirements.\n\nAdvanced data analytics company HEAVY.AI today unveiled solutions to put carriers on more even footing. Its initial product, HeavyRF, delivers a next-generation network planning and operations tool based on the NVIDIA Omniverse platform for creating digital twins .\n\n\u201cBuilding out 5G networks globally will cost trillions of dollars over the next decade, and our telco network customers are rightly worried about how much of that is money not well spent,\u201d said Jon Kondo, CEO of HEAVY.AI. \u201cUsing HEAVY advanced analytics and NVIDIA Omniverse-based real-time simulations, they\u2019ll see big savings in time and money.\u201d\n\nHEAVY.AI also announced that Charter Communications is collaborating on incorporating the tool into its modeling and planning operations for its Spectrum telco network, which has 32 million customers in 41 U.S. states. The collaboration extends HEAVY\u2019s relationship with Charter, building on the existing analytics operations to 5G network planning.\n\n\u201cHEAVY.AI\u2019s new digital twin capabilities give us a way to explore and fine-tune our expanding 5G networks in ways that weren\u2019t possible before,\u201d said Jared Ritter, senior director of analytics and automation at Charter Communications.\n\nWithout the digital twin approach, telco operators must either: physically place microcell towers in densely populated areas to understand the interaction between radio transmitters, the environment, and humans and devices that are on the move \u2014 or use tools that offer less detail about key factors such as tree density or high-rise interference.\n\nEarly deployments of 5G needed 300% more base stations for the same level of coverage offered by the previous generation, called Long Term Evolution (LTE), because of higher spectrum bands. A 5G site will consume 300% more power and cost 4x more than an LTE site if they\u2019re deployed in the same way, according to researcher Analysys Mason.\n\nThose sobering figures are prompting the industry to look for efficiencies. Harnessing GPU-accelerated analytics and real-time geophysical mapping, HEAVY.AI\u2019s digital twin solution allows telcos to test radio frequency (RF) propagation scenarios in seconds, powered by the HeavyRF module. This results in significant time and cost savings, because the base stations and microcells can be more accurately placed and tuned at first installation.\""
  },
  {
    "question": "What is the name of the NVIDIA platform that enables the simulation of a wide range of real-world driving scenarios for connected and autonomous vehicles?",
    "document": "T1ZYIENvbXB1dGluZyBTeXN0ZW1zIDkvMjAvMjIucGRm.pdf",
    "ground_truth_answer": "NVIDIA DRIVE Sim.",
    "ground_truth_context": "\"\n\u201cPlanning our factories of the future starts with building state-of-the-art digital twins using NVIDIA Omniverse,\u201d said J\u00fcrgen Wittmann, head of innovation and virtual production at BMW Group. \u201cUsing NVIDIA OVX systems to run our digital twin workloads will provide the performance and scale needed to develop large-scale photorealistic models of our factories and conduct true-to-reality simulations that will transform our manufacturing, design and production processes.\u201d\n\n\u201cNVIDIA OVX and DRIVE Sim deliver a powerful platform that enables us to simulate a wide range of real-world driving scenarios to safely and efficiently test our next generation of connected and autonomous vehicles as well as to recreate the customer journey to demonstrate vehicle features and functions,\u201d said Alex Heslop, director of electrical, electronic and software engineering at Jaguar Land Rover. \u201cUsing this technology to generate large volumes of high-fidelity, physically accurate scenarios in a scalable, cost-efficient manner will accelerate our progress towards our goal of a future with zero accidents and less congestion.\u201d\n\nComputing System Specifications Each OVX server node combines eight NVIDIA L40 GPUs with three NVIDIA ConnectX-7 network adapters, bringing the power of 100/200/400G networking. For Omniverse workloads that require a higher level of performance and scale, the servers can be deployed in NVIDIA OVX POD and SuperPOD configurations with the NVIDIA Spectrum\u2122-3 Ethernet platform.\n\nAvailability Second-generation NVIDIA OVX systems will be available from Inspur, Lenovo and Supermicro by early 2023, with GIGABYTE, H3C and QCT offering them in the future.\n\nTo learn more about NVIDIA OVX, watch NVIDIA founder and CEO Jensen Huang\u2019s GTC 2022 keynote. Register for GTC for free to attend sessions with NVIDIA and industry leaders.\n\nAbout NVIDIA Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company\u2019s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics and ignited the era of modern AI. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry. More information at https://nvidianews.nvidia.com/.\""
  },
  {
    "question": "What is the name of the new lab being built by NVIDIA, J\u00fclich Supercomputing Centre, and ParTec?",
    "document": "TlZJRElBIEp1bGljaCA1LzIxLzIzLnBkZg==.pdf",
    "ground_truth_answer": "The name of the new lab is the J\u00fclich UNified Infrastructure for Quantum Computing (JUNIQ).",
    "ground_truth_context": "\"\nNVIDIA, J\u00fclich Supercomputing Centre and ParTec to Build Quantum Computing Lab\n\nMajor Collaboration to Fuel Research on NVIDIA-Accelerated Systems Running HPC and Quantum Computing Workloads\n\nISC\u2014In a major step forward for the field of hybrid quantum-classical computing, NVIDIA today announced plans to build a new lab with the J\u00fclich Supercomputing Centre (JSC) at Forschungszentrum J\u00fclich (FZJ) that will feature a classical- quantum supercomputer in partnership with ParTec AG, Munich, based on the NVIDIA\u00ae quantum computing platform.\n\nFZJ, one of the largest interdisciplinary research centers in Europe, will host the lab as part of the J\u00fclich UNified Infrastructure for Quantum Computing (JUNIQ) to run high-performance and low-latency quantum-classical computing workloads. JUNIQ is currently using the JUWELS booster system with 3,744 NVIDIA A100 Tensor Core GPUs for quantum computing simulations.\n\nThe NVIDIA quantum computing platform enables tight integration of quantum and classical computing through the open- source CUDA\u00ae Quantum programming model and world-class simulation through the NVIDIA cuQuantum software development kit.\n\nJSC plans to use a phased approach to test the system and will use the NVIDIA CUDA Quantum programming model to program quantum processors and integrate them within the J\u00fclich exascale modular supercomputing architecture.\n\n\u201cUnifying quantum computing and GPU supercomputing is a key part of enabling the scientific breakthroughs of tomorrow,\u201d said Timothy Costa, director of HPC and quantum at NVIDIA. \u201cNVIDIA\u2019s collaboration with innovators such as the J\u00fclich Supercomputing Centre and ParTec represents an important milestone for quantum-classical computing, making it accessible to countless new researchers and bringing the first quantum-accelerated supercomputer one step closer.\u201d\n\n\u201cHybrid quantum-classical systems are bringing quantum computing closer to reality to solve complex problems that classical computing alone is unable to do,\u201d said Kristel Michielsen, head of the quantum information processing group at JSC. \u201cBy partnering with NVIDIA on the modular quantum computing laboratory, JSC\u2019s researchers can make unprecedented strides in chemistry and material sciences that drive broader, transformative progress across science disciplines and industries.\u201d\n\n\u201cParTec has a long history as a driving force in developing the Modular Supercomputing Architecture with its world-class ParaStation Modulo software enabling hybrid, modular computing,\u201d said Bernhard Frohwitter, CEO of ParTec AG. \u201cQuantum computers will be an essential element of any future heterogeneous supercomputer. This development will open totally new possibilities.\u201d\n\nLearn more about the NVIDIA quantum computing platform at ISC.\""
  },
  {
    "question": "Who is the senior cloud and machine learning solutions architect at NVIDIA?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTAvMTMvYWktYWR2YW5jZXMtb3JhY2xlLWNsb3Vkd29ybGQv.pdf",
    "ground_truth_answer": "Richard Wang.",
    "ground_truth_context": "\"\nMLOps at Scale With Kubeflow on Oracle Cloud Infrastructure \u2014 featuring Richard Wang, senior cloud and machine learning solutions architect at NVIDIA, and Sesh Dehalisan, distinguished cloud architect at Oracle. This session takes place on Tuesday, Oct. 18, from 12:15-1 p.m. PT.\n\nNext-Generation AI Empowering Human Expertise \u2014 featuring Bryan Catanzaro, vice president of applied deep learning research at NVIDIA; Erich Elsen, co-founder and head of machine learning at Adept AI; and Rich Clayton, vice president of product strategy for analytics at Oracle. This session takes place on Tuesday, Oct. 18, from 12:30-1 p.m. PT.\n\nNVIDIA\u2019s Migration From On-Premises to MySQL HeatWave \u2014 featuring Chris May, senior manager at NVIDIA; Radha Chinnaswamy, consultant at NVIDIA; and Sastry Vedantam, MySQL master principal solution engineer at Oracle. This session takes place on Tuesday, Oct. 18, from 4-4:45 p.m. PT.\n\nScale Large Language Models With NeMo Megatron \u2014 featuring Richard Wang, senior cloud and machine learning solutions architect at NVIDIA; Anup Ojah, senior manager of cloud engineering at Oracle; and Tanina Cadwell, solutions architect at Vyasa Analytics . This session takes place on Wednesday, Oct. 19, from 11:30 a.m. to 12:15 p.m. PT.\n\nServe ML Models at Scale With Triton Inference Server on OCI \u2014 featuring Richard Wang, senior cloud and machine learning solutions architect at NVIDIA, and Joanne Lei, master principal cloud architect at Oracle. This session takes place on Wednesday, Oct. 19, from 1:15-2 p.m. PT.\n\nAccelerating Java on the GPU \u2014 featuring Ken Hester, solutions architect director at NVIDIA, and Paul Sandoz, Java architect at Oracle. This session takes place on Thursday, Oct. 20, from 10:15-10:45 a.m. PT.\n\nNVIDIA AI Software for Business Outcomes: Integrating NVIDIA AI Into Your Applications \u2014 featuring Kari Briski, vice president of software product management for AI and high-performance computing software development kits at NVIDIA. This session takes place on demand.\n\nVisit NVIDIA\u2019s Oracle CloudWorld showcase page to discover more about NVIDIA and Oracle\u2019s collaboration and innovations for cloud-based solutions.\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/10/13/ai-advances-oracle-cloudworld/\""
  },
  {
    "question": "What is the name of the company that invented the GPU in 1999?",
    "document": "SmV0c29uIEFHWCBPcmluIDMvMjIvMjIucGRm.pdf",
    "ground_truth_answer": "The company that invented the GPU in 1999 is NVIDIA.",
    "ground_truth_context": "\"\nAbout NVIDIA NVIDIA\u2019s (NASDAQ: NVDA) invention of the GPU in 1999 sparked the growth of the PC gaming market and has redefined modern computer graphics, high performance computing and artificial intelligence. The company\u2019s pioneering work in accelerated computing and AI is reshaping trillion-dollar industries, such as transportation, healthcare and manufacturing, and fueling the growth of many others. More information at https://nvidianews.nvidia.com/.\n\nCertain statements in this press release including, but not limited to, statements as to: the benefits, impact, performance, specifications and availability of our products and technologies, including Jetson AGX Orin; AI transforming manufacturing, healthcare, retail, transportation, smart cities and other essential sectors of the economy; demand for processing continuing to surge; the next generation of robotics and edge AI products; and advances in edge AI and robotics reshaping entire industries are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing product and technologies; market acceptance of our products or our partners products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the companys website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.\n\n\u00a9 2022 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, CUDA-X, Jetson, Jetson AGX Orin, Jetson AGX Xavier, NGC, NVIDIA Isaac, NVIDIA JetPack and NVIDIA Omniverse are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. All other trademarks and copyrights are the property of their respective owners. Features, pricing, availability, and specifications are subject to change without notice.\n\nDavid Pinto +1-408-566-6950 dpinto@nvidia.com\""
  },
  {
    "question": "What software did Ben Mauro use to create the 3D trailer for Huxley?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDkvMTMvaW4tdGhlLW52aWRpYS1zdHVkaW8tc2VwdGVtYmVyLTEzLw==.pdf",
    "ground_truth_answer": "Ben Mauro used Blender software to create mockups and block out scenes for the 3D trailer of Huxley.",
    "ground_truth_context": "\"\nConcept Designer Ben Mauro Delivers Epic 3D Trailer \u2018Huxley\u2019 This Week \u2018In the NVIDIA Studio\u2019 Learn how the sci-fi comic was transformed into a gripping trailer, enabled by close artist collaboration and NVIDIA GeForce RTX GPUs.\n\nAuthor: Gerardo Delgado\n\nEditor\u2019s note: This post is part of our weekly In the NVIDIA Studio series, which celebrates featured artists, offers creative tips and tricks, and demonstrates how NVIDIA Studio technology accelerates creative workflows.\n\nThe gripping sci-fi comic Huxley was brought to life in an action-packed 3D trailer full of excitement and intrigue this week In the NVIDIA Studio .\n\n3D artist, concept designer and storyteller Ben Mauro has contributed to some of the world\u2019s biggest entertainment franchises. He\u2019s worked on movies like Elysium , Valerian and Metal Gear Solid , as well as video games such as Halo Infinite and Call of Duty: Black Ops III .\n\nMauro has met many inspirational artists throughout his storied career, and he collaborated with a few of them to bring Huxley to life. He called the 3D trailer a year\u2019s worth of work, worth every minute spent \u2014 following his decade-long process of creating the comic itself.\n\nIn Mauro\u2019s fantastical, fictional world, two post-apocalyptic scavengers stumble upon a forgotten treasure map in the form of an ancient sentient robot, finding themselves amidst a mystery of galactic scale.\n\nIn designing Huxley the comic, Mauro worked old-school magic with a pad and pencil, sketching characters and environments before importing visuals into Adobe Photoshop. His NVIDIA GeForce RTX 3090 GPU provided fast performance and AI features to speed up his creative workflow.\n\nThe artist used Photoshop\u2019s \u201cArtboards\u201d to quickly view reference artwork for inspiration, as well as \u201cImage Size\u201d to preserve critical details \u2014 both features accelerated by his GPU. To finish up the comic, Mauro turned to Blender software to create mockups and block out scenes with the intention of later converting back to 3D from 2D.\n\nWith 3D trailer production in progress, matte painter and environment artist Steve Cormann used Mauro\u2019s Blender models as a convenient starting point, virtually a one-to-one match to the desired 3D outcome.\n\nCormann, who specializes in Autodesk 3ds Max software, applied advanced modeling techniques in building the scene. 3ds Max has a GPU-accelerated viewport that guarantees fast and interactive 3D modeling. It also lets artists choose their preferred 3D renderer \u2014 which in Cormann\u2019s case is Maxon\u2019s Redshift, where combining GPU acceleration and AI-powered OptiX denoising resulted in lightning-fast final-frame rendering.\n\nThis proved useful as Cormann exported scenes into Adobe Substance 3D Painter to apply various textures and colors. RTX-accelerated light- and ambient-occlusion features baked and optimized assets within the scenes in mere seconds, giving Cormann the option to experiment with different visual aesthetics quickly and easily.\""
  },
  {
    "question": "What is the name of the largest supercomputer used in the study on energy efficiency?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDUvMjEvZ3B1LWVuZXJneS1lZmZpY2llbmN5LW5lcnNjLw==.pdf",
    "ground_truth_answer": "Perlmutter",
    "ground_truth_context": "\"\nWhat\u2019s Up? Watts Down \u2014 More Science, Less Energy Applications on one of the world\u2019s largest supercomputers demonstrate NVIDIA GPUs lead in energy efficiency.\n\nAuthor: Dion Harris\n\nPeople agree: accelerated computing is energy-efficient computing.\n\nThe National Energy Research Scientific Computing Center ( NERSC ), the U.S. Department of Energy\u2019s lead facility for open science, measured results across four of its key high performance computing and AI applications.\n\nThey clocked how fast the applications ran and how much energy they consumed on CPU-only and GPU-accelerated nodes on Perlmutter , one of the world\u2019s largest supercomputers using NVIDIA GPUs.\n\nThe results were clear. Accelerated with NVIDIA A100 Tensor Core GPUs , energy efficiency rose 5x on average. An application for weather forecasting logged gains of 9.8x.\n\nOn a server with four A100 GPUs, NERSC got up to 12x speedups over a dual-socket x86 server.\n\nThat means, at the same performance level, the GPU-accelerated system would consume 588 megawatt-hours less energy per month than a CPU-only system. Running the same workload on a four-way NVIDIA A100 cloud instance for a month, researchers could save more than $4 million compared to a CPU-only instance.\n\nThe results are significant because they\u2019re based on measurements of real-world applications, not synthetic benchmarks.\n\nThe gains mean that the 8,000+ scientists using Perlmutter can tackle bigger challenges, opening the door to more breakthroughs.\n\nAmong the many use cases for the more than 7,100 A100 GPUs on Perlmutter, scientists are probing subatomic interactions to find new green energy sources.\n\nThe applications NERSC tested span molecular dynamics, material science and weather forecasting.\n\nFor example, MILC simulates the fundamental forces that hold particles together in an atom. It\u2019s used to advance quantum computing, study dark matter and search for the origins of the universe.\n\nBerkeleyGW helps simulate and predict optical properties of materials and nanostructures, a key step toward developing more efficient batteries and electronic devices.\n\nEXAALT, which got an 8.5x efficiency gain on A100 GPUs, solves a fundamental challenge in molecular dynamics. It lets researchers simulate the equivalent of short videos of atomic movements rather than the sequences of snapshots other tools provide.\n\nThe fourth application in the tests, DeepCAM, is used to detect hurricanes and atmospheric rivers in climate data. It got a 9.8x gain in energy efficiency when accelerated with A100 GPUs.\n\nThe NERSC results echo earlier calculations of the potential savings with accelerated computing. For example, in a separate analysis NVIDIA conducted, GPUs delivered 42x better energy efficiency on AI inference than CPUs.\n\nThat means switching all the CPU-only servers running AI worldwide to GPU-accelerated systems could save a whopping 10 trillion watt-hours of energy a year. That\u2019s like saving the energy 1.4 million\n\nhomes consume in a year.\""
  },
  {
    "question": "How does the Audio2Face add-on in Blender work?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDIvMTUvYmxlbmRlci1hbHBoYS1yZWxlYXNlLW9tbml2ZXJzZS8=.pdf",
    "ground_truth_answer": "The Audio2Face add-on in Blender uses AI to automatically generate realistic facial expressions from an audio file, making it easier for artists to animate characters without needing to be a technical rigger or animator.",
    "ground_truth_context": "\"\nBlender Alpha Release Comes to Omniverse, Introducing Scene Optimization Tools, Improved AI-Powered Character Animation New Blender add-ons let creators reimagine virtual worlds and animate lifelike characters with ease.\n\nAuthor: Dane Johnston\n\nWhether creating realistic digital humans that can express emotion or building immersive virtual worlds, 3D artists can reach new heights with NVIDIA Omniverse , a platform for creating and operating metaverse applications.\n\nA new Blender alpha release, now available in the Omniverse Launcher , lets users of the 3D graphics software optimize scenes and streamline workflows with AI-powered character animations.\n\nThe new scene optimization add-on in the Blender release enables creators to fix bad geometry and generate automatic UVs , or 2D maps of 3D objects. It also reduces the number of polygons that need to be rendered to increase the scene\u2019s overall performance, which significantly brings down file size, as well as CPU and GPU memory usage.\n\nPlus, anyone can now accomplish what used to require a technical rigger or animator using an Audio2Face add-on.\n\nA panel in the add-on makes it easier to use Blender characters in Audio2Face, an AI-enabled tool that automatically generates realistic facial expressions from an audio file.\n\nThis new functionality eases the process of bringing generated face shapes back onto rigs \u2014 that is, digital skeletons \u2014 by applying shapes exported through the Universal Scene Description ( USD ) framework onto a character even if it is fully rigged, meaning its whole body has a working digital skeleton. The integration of the facial shapes doesn\u2019t alter the rigs, so Audio2Face shapes and animation can be applied to characters \u2014 whether for games, shows and films, or simulations \u2014 at any point in the artist\u2019s workflow.\n\nAudio2Face puts AI-powered facial animation in the hands of every Blender user who works with Omniverse.\n\nUsing the new Blender add-on for Audio2Face , animator and popular YouTuber Marko Matosevic, aka Markom 3D , rigged and animated a Battletoads -inspired character using just an audio file.\n\nAustralia-based Matosevic joined Dave Tyner, a technical evangelist at NVIDIA, on a livestream to showcase their live collaboration across time zones, connecting 3D applications in a real-time Omniverse jam session. The two used the new Blender alpha release with Omniverse to make progress on one of Matosevic\u2019s short animations.\n\nThe new Blender release was also on display last month at CES in The Artists\u2019 Metaverse, a demo featuring seven artists, across time zones, who used Omniverse Nucleus Cloud , Autodesk, SideFX, Unreal Engine and more to create a short cinematic in real time.\n\nCreators can save time and simplify processes with the add-ons available in Omniverse\u2019s Blender build.\n\nNVIDIA principal artist Zhelong Xu, for example, used Blender and Omniverse to visualize an NVIDIA-themed \u201cYear of the Rabbit\u201d zodiac.\""
  },
  {
    "question": "What is the name of the newly launched AI platform by NVIDIA?",
    "document": "TmV3IEdlRm9yY2UgTGFwdG9wcyBhbmQgRGVza3RvcHMgMS80LzIyLnBkZg==.pdf",
    "ground_truth_answer": "The newly launched AI platform by NVIDIA is called NVIDIA Omniverse.",
    "ground_truth_context": "\"\n\u00a9 2022 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, GauGAN2, GeForce, GeForce NOW, GeForce RTX, G-SYNC, NVIDIA Omniverse and NVIDIA TITAN RTX are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. MAXQ is the registered trademark of Maxim Integrated Products. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability and specifications are subject to change without notice.\n\nKelly Musgrave Senior Manager, Consumer PR NVIDIA Corporation +1-650-421-3748 kmusgrave@nvidia.com\""
  },
  {
    "question": "What is the name of the large language model that paved the way for generative AI?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDQvMDUvaW5mZXJlbmNlLW1scGVyZi1haS8=.pdf",
    "ground_truth_answer": "BERT",
    "ground_truth_context": "\"\nNVIDIA Takes Inference to New Heights Across MLPerf Tests\n\nNVIDIA H100 and L4 GPUs took generative AI and all other workloads to new levels in the latest MLPerf benchmarks, while Jetson AGX Orin made performance and efficiency gains.\n\nAuthor: Dave Salvator\n\nMLPerf remains the definitive measurement for AI performance as an independent, third-party benchmark. NVIDIA\u2019s AI platform has consistently shown leadership across both training and inference since the inception of MLPerf, including the MLPerf Inference 3.0 benchmarks released today.\n\n\u201cThree years ago when we introduced A100, the AI world was dominated by computer vision. Generative AI has arrived,\u201d said NVIDIA founder and CEO Jensen Huang.\n\n\u201cThis is exactly why we built Hopper, specifically optimized for GPT with the Transformer Engine. Today\u2019s MLPerf 3.0 highlights Hopper delivering 4x more performance than A100.\n\n\u201cThe next level of Generative AI requires new AI infrastructure to train large language models with great energy efficiency. Customers are ramping Hopper at scale, building AI infrastructure with tens of thousands of Hopper GPUs connected by NVIDIA NVLink and InfiniBand.\n\n\u201cThe industry is working hard on new advances in safe and trustworthy Generative AI. Hopper is enabling this essential work,\u201d he said.\n\nThe latest MLPerf results show NVIDIA taking AI inference to new levels of performance and efficiency from the cloud to the edge.\n\nSpecifically, NVIDIA H100 Tensor Core GPUs running in DGX H100 systems delivered the highest performance in every test of AI inference, the job of running neural networks in production. Thanks to software optimizations , the GPUs delivered up to 54% performance gains from their debut in September.\n\nIn healthcare, H100 GPUs delivered a 31% performance increase since September on 3D-UNet, the MLPerf benchmark for medical imaging.\n\nPowered by its Transformer Engine , the H100 GPU, based on the Hopper architecture, excelled on BERT, a transformer-based large language model that paved the way for today\u2019s broad use of generative AI.\n\nGenerative AI lets users quickly create text, images, 3D models and more. It\u2019s a capability companies from startups to cloud service providers are rapidly adopting to enable new business models and accelerate existing ones.\n\nHundreds of millions of people are now using generative AI tools like ChatGPT \u2014 also a transformer model \u2014 expecting instant responses.\n\nAt this iPhone moment of AI, performance on inference is vital. Deep learning is now being deployed nearly everywhere, driving an insatiable need for inference performance from factory floors to online recommendation systems .\n\nNVIDIA L4 Tensor Core GPUs made their debut in the MLPerf tests at over 3x the speed of prior-generation T4 GPUs. Packaged in a low-profile form factor, these accelerators are designed to deliver high throughput and low latency in almost any server.\""
  },
  {
    "question": "What is Replit's goal for software creation?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDgvMTYvcmVwbGl0LWNlby1hbWphZC1tYXNhZC1vbi1lbXBvd2VyaW5nLXRoZS1uZXh0LWJpbGxpb24tc29mdHdhcmUtY3JlYXRvcnMv.pdf",
    "ground_truth_answer": "Replit's goal is to empower the next billion software creators by reducing the friction between an idea and a software product.",
    "ground_truth_context": "\"\nReplit CEO Amjad Masad on Empowering the Next Billion Software Creators\n\nAuthor: Kristen Yee\n\nReplit aims to empower the next billion software creators.\n\nIn this week\u2019s episode of NVIDIA\u2019s AI Podcast , host Noah Kravitz dives into a conversation with Replit CEO Amjad Masad. Masad says the San Francisco-based maker of a software development platform, which came up as a member of NVIDIA\u2019s Inception program for startups, wants to bridge the gap between ideas and software, a task simplified by advances in generative AI.\n\n\u201cReplit is fundamentally about reducing the friction between an idea and a software product,\u201d Masad said.\n\nThe company\u2019s Ghostwriter coding AI has two main features: a code completion model and a chat model. These features not only make suggestions as users type their code, but also provide intelligent explanations of what a piece of code is doing, tracing dependencies and context. The model can even flag errors and offer solutions \u2014 like a full collaborator in a Google Docs for code.\n\nThe company is also developing \u201cmake me an app\u201d functionality. This tool allows users to provide high-level instructions to an Artificial Developer Intelligence, which then builds, tests and iterates the requested software.\n\nThe aim is to make software creation accessible to all, even those with no coding experience. While this feature is still under development, Masad said the company plans to improve it over the next year, potentially having it ready for developers in the next six to eight months.\n\nGoing forward, Masad envisions a future where AI functions as a collaborator, able to conduct high-level tasks and even manage resources. \u201cWe\u2019re entering a period where software is going to feel more alive,\u201d Masad said. \u201cAnd so I think computing is becoming more humane, more accessible, more exciting, more natural.\u201d <\n\nh2>You Might Also Like\n\nJules Anh Tuan Nguyen Explains How AI Lets Amputee Control Prosthetic Hand, Video Games A postdoctoral researcher at the University of Minnesota discusses his efforts to allow amputees to control their prosthetic limb \u2014 right down to the finger motions \u2014 with their minds.\n\nOverjet\u2019s Ai Wardah Inam on Bringing AI to Dentistry Overjet, a member of NVIDIA Inception , is moving fast to bring AI to dentists\u2019 offices. Dr. Wardah Inam, CEO of the company, discusses using AI to improve patient care.\n\nImmunai CTO and Co-Founder Luis Voloch on Using Deep Learning to Develop New Drugs Luis Voloch, co-founder and chief technology officer of Immunai, talks about tackling the challenges of the immune system with a machine learning and data science mindset.\n\nIn addition to Amazon Music , get the AI Podcast through iTunes , Google Podcasts , Google Play , Castbox , DoggCatcher, Overcast , PlayerFM , Pocket Casts, Podbay , PodBean , PodCruncher, PodKicker, Soundcloud , Spotify , Stitcher and TuneIn .\n\nMake the AI Podcast better. Have a few minutes to spare? Fill out this listener survey .\""
  },
  {
    "question": "What is the name of the software development kit used by PennyLane to accelerate quantum simulations?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDkvMTIvcXVhbnR1bS1zdXBlcmNvbXB1dGVycy1wZW5ueWxhbmUv.pdf",
    "ground_truth_answer": "NVIDIA cuQuantum",
    "ground_truth_context": "\"\nA Quantum Boost: cuQuantum With PennyLane Lets Simulations Ride Supercomputers Scientists are accelerating quantum simulations for the first time at supercomputing scale, thanks to NVIDIA cuQuantum with Xanadu\u2019s PennyLane.\n\nAuthor: Sam Stanwyck\n\nTen miles in from Long Island\u2019s Atlantic coast, Shinjae Yoo is revving his engine.\n\nThe computational scientist and machine learning group lead at the U.S. Department of Energy\u2019s Brookhaven National Laboratory is one of many researchers gearing up to run quantum computing simulations on a supercomputer for the first time, thanks to new software.\n\nYoo\u2019s engine, the Perlmutter supercomputer at the National Energy Research Scientific Computing Center (NERSC), is using the latest version of PennyLane , a quantum programming framework from Toronto-based Xanadu. The open-source software, which builds on the NVIDIA cuQuantum software development kit , lets simulations run on high-performance clusters of NVIDIA GPUs.\n\nThe performance is key because researchers like Yoo need to process ocean-size datasets. He\u2019ll run his programs across as many as 256 NVIDIA A100 Tensor Core GPUs on Perlmutter to simulate about three dozen qubits \u2014 the powerful calculators quantum computers use.\n\nThat\u2019s about twice the number of qubits most researchers can model these days.\n\nThe so-called multi-node version of PennyLane, used in tandem with the NVIDIA cuQuantum SDK, simplifies the complex job of accelerating massive simulations of quantum systems.\n\n\u201cThis opens the door to letting even my interns run some of the largest simulations \u2014 that\u2019s why I\u2019m so excited,\u201d said Yoo, whose team has six projects using PennyLane in the pipeline.\n\nHis work aims to advance high-energy physics and machine learning. Other researchers use quantum simulations to take chemistry and materials science to new levels.\n\nQuantum computing is alive in corporate R&D; centers, too.\n\nFor example, Xanadu is helping companies like Rolls-Royce develop quantum algorithms to design state-of-the-art jet engines for sustainable aviation and Volkswagen Group invent more powerful batteries for electric cars.\n\nFour More Projects on Perlmutter\n\nMeanwhile, at NERSC, at least four other projects are in the works this year using multi-node Pennylane, according to Katherine Klymko, who leads the quantum computing program there. They include efforts from NASA Ames and the University of Alabama.\n\n\u201cResearchers in my field of chemistry want to study molecular complexes too large for classical computers to handle,\u201d she said. \u201cTools like Pennylane let them extend what they can currently do classically to prepare for eventually running algorithms on large-scale quantum computers.\u201d\n\nPennyLane is the product of a novel idea. It adapts popular deep learning techniques like backpropagation and tools like PyTorch to programming quantum computers.\""
  },
  {
    "question": "Which GPU is recommended for video editing and 3D modeling?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDIvMjIvaW4tdGhlLW52aWRpYS1zdHVkaW8tZmVicnVhcnktMjIv.pdf",
    "ground_truth_answer": "The GeForce RTX 4060 GPU is recommended for video editing and 3D modeling.",
    "ground_truth_context": "\"\nThe GeForce RTX 4060 GPU-class laptops equipped with 8GB of video memory are great for video editing and artists looking to get started in 3D modeling and animation. In the popular open-source 3D app Blender, render times are a whopping 38% faster than the last generation.\n\nGet started with GPU acceleration for photography, graphic design and video editing workflows using GeForce RTX 4050 GPUs, which provide a massive upgrade from integrated graphics. Access accelerated AI features, including 54% faster performance in Topaz Video for upscaling and deinterlacing footage. And turn home offices into professional-grade studios with NVIDIA\u2019s encoder and\n\nthe AI-powered NVIDIA Broadcast app for livestreaming.\n\nFreelancers, hobbyists, aspiring artists and others can find a GeForce RTX GPU to fit their needs, now available in the new lineup of NVIDIA Studio laptops .\n\nSamsung\u2019s Galaxy Book3 Ultra comes with a choice of the GeForce RTX 4070 or 4050 GPU, alongside a vibrant 16-inch, 3K, AMOLED display.\n\nPick one up at Best Buy or on Samsung.com .\n\nGIGABYTE upgraded its Aero 16 Studio laptop with up to a GeForce RTX 4070 GPU and a 16-inch, thin-bezel, 60Hz, OLED display. The Aero 14 features a GeForce RTX 4050 GPU with a 14-inch, thin-bezel, 90Hz, OLED display.\n\nPurchase the Aero 14 from Amazon , and find both laptops on GIGABYTE.com .\n\nThe ASUS ROG FLOW Z13 comes with up to a GeForce RTX 4060 GPU, QHD, 165Hz, 13.4-inch Nebula display, as well as a 170-degree kickstand and detachable full-sized keyboard for portable creating, plus a stylus with NVIDIA Canvas support to turn simple brushstrokes into realistic images powered by AI.\n\nGet one from ASUS.com .\n\nMSI\u2019s Stealth 17 Studio and Razer\u2019s 16 and 18 models, with up to GeForce RTX 4090 Laptop GPUs, are also available to pick up today.\n\nStudio laptops power the imaginations of the world\u2019s most creative minds, including this week\u2019s In the NVIDIA Studio artist, Shangyu Wang.\n\nFrom the moment his movie\u2019s opening credits roll, viewers can expect to be captivated by a spellbinding journey in space and an intricately designed world, complemented by engaging music and voice-overs.\n\nThe film, Most Precious Gift , centers on humanity attempting to make peace with another intelligent lifeform holding the key to survival. It\u2019s an extension of Wang\u2019s interests in alien civilizations and their potential conflicts with humankind.\n\nWang usually jumps directly into 3D modeling, bypassing the concept stage that most artists go through. He sculpts and shapes the models in Autodesk Maya and Autodesk Fusion 360.\n\nBy selecting the default Autodesk Arnold renderer, using his GeForce RTX 3080 Ti-powered Studio laptop, Wang was able to use RTX-accelerated ray tracing and AI denoising, which let him tinker with and add details to highly interactive, photorealistic visuals. This was a boon for his efficiency.\""
  },
  {
    "question": "What is the name of the software suite used for secondary genomic analysis of next-generation sequencing data during the exome sequencing process by Regeneron Genetics Center?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDEvMjYvdWstYmlvYmFuay1hZHZhbmNlcy1nZW5vbWljcy1yZXNlYXJjaC1jbGFyYS1wYXJhYnJpY2tzLw==.pdf",
    "ground_truth_answer": "NVIDIA Clara Parabricks",
    "ground_truth_context": "\"\nUK Biobank Advances Genomics Research with NVIDIA Clara Parabricks World\u2019s largest repository of deidentified data for genetics research is providing scientists access to NVIDIA Clara Parabricks to fuel accelerated genomics and drug discovery.\n\nAuthor: Craig Rhodes\n\nUK Biobank is broadening scientists\u2019 access to high-quality genomic data and analysis by making its massive dataset available in the cloud alongside NVIDIA GPU-accelerated analysis tools.\n\nUsed by more than 25,000 registered researchers around the world, UK Biobank is a large-scale biomedical database and research resource with deidentified genetic datasets, along with medical imaging and health record data, from more than 500,000 participants across the U.K.\n\nRegeneron Genetics Center, the high-throughput sequencing center of biotech leader Regeneron, recently teamed up with UK Biobank to sequence and analyze the exomes \u2014 all protein-coding portions of the genome \u2014 of all the biobank participants.\n\nThe Regeneron team used NVIDIA Clara Parabricks , a software suite for secondary genomic analysis of next-generation sequencing data, during the exome sequencing process.\n\nUK Biobank has released 450,000 of these exomes for access by approved researchers, and is now providing scientists six months of free access to Clara Parabricks through its cloud-based Research Analysis Platform. It was developed by bioinformatics platform DNAnexus, which lets scientists use Clara Parabricks running on NVIDIA GPUs in the AWS cloud.\n\n\u201cAs demonstrated by Regeneron, GPU acceleration with Clara Parabricks achieves the throughputs, speed and reproducibility needed when processing genomic datasets at scale,\u201d said Dr. Mark Effingham, deputy CEO of UK Biobank. \u201cThere are a number of research groups in the U.K. who were pushing for these accelerated tools to be available in our platform for use with our extensive dataset.\u201d\n\nRegeneron\u2019s researchers used the DeepVariant Germline Pipeline from NVIDIA Clara Parabricks to run their analysis with a model specific to the genetic center\u2019s workflow.\n\nIts researchers identified 12 million coding variants and hundreds of genes associated with health-related traits \u2014 certain genes were associated with increased risk for liver disease and eye disease, and others were linked to lower risk of diabetes and asthma.\n\nThe unique set of tools the researchers used for high-quality variant detection is available to UK Biobank registered users through the Research Analysis Platform . This capability will allow scientists to harmonize their own exome data with sequenced exome data from UK Biobank by running the same bioinformatics pipeline used to generate the initial reference dataset.\n\nResearchers deciphering the genetic codes of humans \u2014 and of the viruses and bacteria that infect humans \u2014 can often be limited by the computational resources available to them.\""
  },
  {
    "question": "What is the name of the research team that developed a state-of-the-art model for predicting COVID variants?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTEvMTQvZ2Vub21pYy1sYXJnZS1sYW5ndWFnZS1tb2RlbC1wcmVkaWN0cy1jb3ZpZC12YXJpYW50cy8=.pdf",
    "ground_truth_answer": "The research team was led by Arvind Ramanathan, a computational biologist at Argonne National Laboratory, and included researchers from NVIDIA, the University of Chicago, and others.",
    "ground_truth_context": "\"\nSpeaking the Language of the Genome: Gordon Bell Winner Applies Large Language Models to Predict New COVID Variants\n\nResearchers from Argonne National Laboratory, NVIDIA, the University of Chicago and more \u2014 awardees of a Gordon Bell special prize for COVID-19 research \u2014 developed a state-of-the-art model that processes genome-scale data.\n\nAuthor: Geetika Gupta\n\nEditor\u2019s note: This post was updated on November 17 after the announcement of the Gordon Bell prize winners.\n\nThe winner of the Gordon Bell special prize for high performance computing-based COVID-19 research has taught large language models (LLMs) a new lingo \u2014 gene sequences \u2014 that can unlock insights in genomics, epidemiology and protein engineering.\n\nPublished in October , the groundbreaking work is a collaboration by more than two dozen academic and commercial researchers from Argonne National Laboratory, NVIDIA, the University of Chicago and others.\n\nThe research team trained an LLM to track genetic mutations and predict variants of concern in SARS-CoV-2, the virus behind COVID-19. While most LLMs applied to biology to date have been trained on datasets of small molecules or proteins, this project is one of the first models trained on raw nucleotide sequences \u2014 the smallest units of DNA and RNA.\n\n\u201cWe hypothesized that moving from protein-level to gene-level data might help us build better models to understand COVID variants,\u201d said Arvind Ramanathan, computational biologist at Argonne, who led the project. \u201cBy training our model to track the entire genome and all the changes that appear in its evolution, we can make better predictions about not just COVID, but any disease with enough genomic data.\u201d\n\nThe Gordon Bell awards, regarded as the Nobel Prize of high performance computing, were presented at the SC22 conference by the Association for Computing Machinery, which represents around 100,000 computing experts worldwide. Since 2020, the group has awarded a special prize for outstanding research that advances the understanding of COVID with HPC.\n\nLLMs have long been trained on human languages, which usually comprise a couple dozen letters that can be arranged into tens of thousands of words, and joined together into longer sentences and paragraphs. The language of biology, on the other hand, has only four letters representing nucleotides \u2014 A, T, G and C in DNA, or A, U, G and C in RNA \u2014 arranged into different sequences as genes.\n\nWhile fewer letters may seem like a simpler challenge for AI, language models for biology are actually far more complicated. That\u2019s because the genome \u2014 made up of over 3 billion nucleotides in humans, and about 30,000 nucleotides in coronaviruses \u2014 is difficult to break down into distinct, meaningful units.\""
  },
  {
    "question": "What is NVIDIA Omniverse?",
    "document": "U2llbWVucyBOVklESUEgNi8yOS8yMi5wZGY=.pdf",
    "ground_truth_answer": "NVIDIA Omniverse is a platform for 3D design, simulation, and collaboration that allows users to create and interact with digital models of buildings, factories, and other complex systems. It uses artificial intelligence and machine learning to enable real-time collaboration and simulation, and is designed to help industries such as architecture, engineering, and construction improve their design and construction processes.",
    "ground_truth_context": "\"\nCertain statements in this press release including, but not limited to, statements as to: the benefits, performance, impact, and abilities of NVIDIA\u2019s products and technologies, including NVIDIA Omniverse and NVIDIA AI; the benefits and impact of the partnership between Siemens and NVIDIA; and the industrial metaverse driving digital transformation are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic conditions; NVIDIA\u2019s reliance on third parties to manufacture, assemble, package and test NVIDIA\u2019s products; the impact of technological development and competition; development of new products and technologies or enhancements to NVIDIA\u2019s existing products and technologies; market acceptance of NVIDIA\u2019s products or NVIDIA\u2019s partners\u2019 products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of NVIDIA\u2019s products or technologies when integrated into systems; as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on NVIDIA\u2019s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.\n\nNote: A list of relevant Siemens trademarks can be found here. NVIDIA, the NVIDIA logo and NVIDIA Omniverse are trademarks and/or registered trademarks of NVIDIA Corporation and/or Mellanox Technologies in the U.S. and other countries. Other trademarks belong to their respective owners.\n\nNoah Cole Siemens noah.cole@siemens.com Kasia Johnston +1-415-813-8859 kasiaj@nvidia.com Lexi Hatziharalambous lexih@nvidia.com\""
  },
  {
    "question": "What was the primary benefit of using Omniverse USD Composer according to Rogelio Olguin?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDQvMTMvZ2Vmb3JjZS1ydHgtNDA3MC1zdHVkaW8tY3JlYXRvcnMv.pdf",
    "ground_truth_answer": "The primary benefit of using Omniverse USD Composer was being able to quickly see what he was doing, and place and compose shots quickly, which made this so simple to work on.",
    "ground_truth_context": "\"\nNext, Maxon\u2019s ZBrush was used to sculpt the main asteroids. The Drop 3D function was especially helpful in increasing the density of local meshes while maintaining high-resolution details.\n\nThen came the animation phase in SideFX Houdini, building animations of the large and tiny cloud-based asteroids alike to ensure constant movement and rotation.\n\nOlguin stressed the importance of his GeForce RTX 40 Series GPU. \u201cVirtually every part of the process relied on RTX GPU technology, including path-traced rendering,\u201d he said. \u201cWithout RTX acceleration, this piece would have been impossible.\u201d\n\nWith all components in place, the team worked in Omniverse USD Composer (formerly known as Create) to assemble complex, physically accurate simulations. They collaboratively edited 3D scenes in real time with ease.\n\n\u201cHaving a beast of a machine has sped up what I can do. I would dread going back to a slower machine.\u201d \u2014 Rogelio Olguin.\n\n\u201cThe primary benefit of using Omniverse USD Composer was being able to quickly see what I was doing, and place and compose our shots quickly, which made this so simple to work on,\u201c said Olguin.\n\nUSD Composer works with the Universal Scene Description (USD) format, enabling artists to choose their 3D app of choice. It supports Autodesk Maya, SideFX Houdini, Trimble SketchUp and more. It also removes pipeline bottlenecks, so there\u2019s no need for artists to constantly download, reformat, upload and download again.\n\nAfter all, using USD Composer to collaborate in 3D is just comet sense.\n\nStay tuned for more updates on Hauler . For more artistic inspiration from Olguin, check out his ArtStation page.\n\nAV1 encoding support is coming to YouTube via OBS. GeForce RTX GPU owners broadcasting on YouTube can expect increased streaming quality. This feature is currently in beta and will be available as a general release in the near future.\n\nFollow NVIDIA Studio on Instagram , Twitter and Facebook . Access tutorials on the Studio YouTube channel and get updates directly in your inbox by subscribing to the Studio newsletter . Learn more about Omniverse on Instagram , Medium , Twitter and YouTube for additional resources and inspiration. Check out the Omniverse forums , and join our Discord server and Twitch channel to chat with the community.\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/04/13/geforce-rtx-4070-studio-creators/\""
  },
  {
    "question": "What is the name of the sci-fi comic that was transformed into a 3D trailer in the NVIDIA Studio?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDkvMTMvaW4tdGhlLW52aWRpYS1zdHVkaW8tc2VwdGVtYmVyLTEzLw==.pdf",
    "ground_truth_answer": "The name of the sci-fi comic is Huxley.",
    "ground_truth_context": "\"\nConcept Designer Ben Mauro Delivers Epic 3D Trailer \u2018Huxley\u2019 This Week \u2018In the NVIDIA Studio\u2019 Learn how the sci-fi comic was transformed into a gripping trailer, enabled by close artist collaboration and NVIDIA GeForce RTX GPUs.\n\nAuthor: Gerardo Delgado\n\nEditor\u2019s note: This post is part of our weekly In the NVIDIA Studio series, which celebrates featured artists, offers creative tips and tricks, and demonstrates how NVIDIA Studio technology accelerates creative workflows.\n\nThe gripping sci-fi comic Huxley was brought to life in an action-packed 3D trailer full of excitement and intrigue this week In the NVIDIA Studio .\n\n3D artist, concept designer and storyteller Ben Mauro has contributed to some of the world\u2019s biggest entertainment franchises. He\u2019s worked on movies like Elysium , Valerian and Metal Gear Solid , as well as video games such as Halo Infinite and Call of Duty: Black Ops III .\n\nMauro has met many inspirational artists throughout his storied career, and he collaborated with a few of them to bring Huxley to life. He called the 3D trailer a year\u2019s worth of work, worth every minute spent \u2014 following his decade-long process of creating the comic itself.\n\nIn Mauro\u2019s fantastical, fictional world, two post-apocalyptic scavengers stumble upon a forgotten treasure map in the form of an ancient sentient robot, finding themselves amidst a mystery of galactic scale.\n\nIn designing Huxley the comic, Mauro worked old-school magic with a pad and pencil, sketching characters and environments before importing visuals into Adobe Photoshop. His NVIDIA GeForce RTX 3090 GPU provided fast performance and AI features to speed up his creative workflow.\n\nThe artist used Photoshop\u2019s \u201cArtboards\u201d to quickly view reference artwork for inspiration, as well as \u201cImage Size\u201d to preserve critical details \u2014 both features accelerated by his GPU. To finish up the comic, Mauro turned to Blender software to create mockups and block out scenes with the intention of later converting back to 3D from 2D.\n\nWith 3D trailer production in progress, matte painter and environment artist Steve Cormann used Mauro\u2019s Blender models as a convenient starting point, virtually a one-to-one match to the desired 3D outcome.\n\nCormann, who specializes in Autodesk 3ds Max software, applied advanced modeling techniques in building the scene. 3ds Max has a GPU-accelerated viewport that guarantees fast and interactive 3D modeling. It also lets artists choose their preferred 3D renderer \u2014 which in Cormann\u2019s case is Maxon\u2019s Redshift, where combining GPU acceleration and AI-powered OptiX denoising resulted in lightning-fast final-frame rendering.\n\nThis proved useful as Cormann exported scenes into Adobe Substance 3D Painter to apply various textures and colors. RTX-accelerated light- and ambient-occlusion features baked and optimized assets within the scenes in mere seconds, giving Cormann the option to experiment with different visual aesthetics quickly and easily.\""
  },
  {
    "question": "What is the name of the ship that sank off the coast of Western Australia during WWII?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTEvMTgvM2Qtc2hpcHdyZWNrcy1wZXJ0aC8=.pdf",
    "ground_truth_answer": "HMAS Sydney (II)",
    "ground_truth_context": "\"\nSee a Sea Change: 3D Researchers Bring Naval History to Life\n\nA half-million pictures of two shipwrecks will blend into lifelike VR/AR exhibits thanks to accelerated computing.\n\nAuthor: Rick Merritt\n\nMuseumgoers will be able to explore two sunken WWII ships as if they were scuba divers on the ocean floor, thanks to work at Curtin University in Perth, Australia.\n\nExhibits in development, for display in Australia and potentially further afield, will use exquisitely detailed 3D models the researchers are creating to tell the story of one of the nation\u2019s greatest naval battles.\n\nOn Nov. 19, 1941, Australia\u2019s HMAS Sydney (II) and Germany\u2019s HSK Kormoran lobbed hundreds of shells in a duel that lasted less than an hour. More than 700 died, including every sailor on the Sydney. Both ships sank 8,000 feet, 130 miles off the coast of Western Australia, not to be discovered for decades.\n\nAndrew Woods, an expert in stereoscopic 3D visualization and associate professor at Curtin, built an underwater rig with more than a dozen video and still cameras to capture details of the wrecks in 2015.\n\nAsh Doshi, a computer vision specialist and senior research officer at Curtin, is developing and running software on NVIDIA GPUs that stitches the half-million pictures and 300 hours of video they took into virtual and printed 3D models.\n\nIt\u2019s hard, pioneering work in a process called photogrammetry . Commercially available software maxes out at around 10,000 images.\n\n\u201cIt\u2019s highly computationally intensive \u2014 when you double the number of images, you quadruple the compute requirements,\u201d said Woods, who manages the Curtin HIVE , a lab with four advanced visualization systems.\n\n\u201cIt would\u2019ve taken a thousand years to process with our existing systems, even though they are fairly fast,\u201d he said.\n\nWhen completed next year, the work will have taken less than three years, thanks to systems at the nearby Pawsey Supercomputing Centre using NVIDIA V100 and prior-generation GPUs.\n\nAccelerated computing is critical because the work is iterative. Images must be processed, manipulated and then reprocessed.\n\nFor example, Woods said a first pass on a batch of 400 images would take 10 hours on his laptop. By contrast, he could run a first pass in 10 minutes on his system with two NVIDIA RTX A6000 GPUs awarded through NVIDIA\u2019s Applied Research Accelerator Program .\n\nIt would take a month to process 8,000 images on the lab\u2019s fast PCs, work the supercomputer could handle in a day. \u201cRarely would anyone in industry wait a month to process a dataset,\u201d said Woods.\n\nLocal curators can\u2019t wait to get the Sydney and Kormoran models on display. Half the comments on their Tripadvisor page already celebrate 3D films the team took of the wrecks.\n\nThe digital models will more deeply engage museumgoers with interactive virtual and augmented reality exhibits and large-scale 3D prints.\n\n\u201cThese 3D models really help us unravel the story, so people can appreciate the history,\u201d Woods said.\""
  },
  {
    "question": "What is the name of the NVIDIA module used for AI computing in the Saildrone?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDcvMTkvc2FpbGRyb25lLWF1dG9ub21vdXMtb2NlYW5pYy1tb25pdG9yaW5nLWpldHNvbi1kZWVwc3RyZWFtLw==.pdf",
    "ground_truth_answer": "The NVIDIA module used for AI computing in the Saildrone is the Jetson AGX Xavier.",
    "ground_truth_context": "\"\nLearn more about NVIDIA Jetson modules and the DeepStream SDK.\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/07/19/saildrone-autonomous-oceanic-monitoring-jetso n-deepstream/\""
  },
  {
    "question": "What is the name of the software that NVIDIA collaborated with Canonical, Red Hat, SUSE, and Siemens on?",
    "document": "SUdYIEVkZ2UgQUkgOS8yMC8yMi5wZGY=.pdf",
    "ground_truth_answer": "NVIDIA collaborated with Canonical, Red Hat, SUSE, and Siemens on the NVIDIA AI Enterprise software.",
    "ground_truth_context": "\"\nCertain statements in this press release including, but not limited to, statements as to: the benefits, performance, impact, and availability of our products and technologies, including NVIDIA IGX, NVIDIA IGX Orin, NVIDIA AI Enterprise software, NVIDIA Fleet Command, NVIDIA Omniverse platform, NVIDIA Metropolis, NVIDIA Clara Holoscan; industries setting new functional safety standards for AI and computing; embedded-computing manufacturers including ADLINK, Advantech, Dedicated Computing, Kontron, Leadtek, Onyx, MBX, Portwell, Prodrive Technologies and YUAN building products based on the IGX design; the benefits, performance and impact of our collaborations including with Canonical, Red Hat, SUSE, and Siemens are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing product and technologies; market acceptance of our products or our partners products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the companys website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.\n\n\u00a9 2022 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, ConnectX, NVIDIA Clara, NVIDIA Fleet Command, and NVIDIA Omniverse are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability and specifications are subject to change without notice.\n\nKristin Uchiyama Enterprise and Edge Computing +1-408-486-2248 kuchiyama@nvidia.com\""
  },
  {
    "question": "How does NVIDIA Iray technology and GeForce RTX 40 Series GPUs benefit 3D artists like Pablo Mu\u00f1oz G\u00f3mez?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTEvMjIvaW4tdGhlLW52aWRpYS1zdHVkaW8tbm92ZW1iZXItMjIv.pdf",
    "ground_truth_answer": "NVIDIA Iray technology and GeForce RTX 40 Series GPUs enable 3D artists like Pablo Mu\u00f1oz G\u00f3mez to edit in real time, use ray-traced baking for faster rendering speeds, and apply realistic effects in real time with interactive ray tracing, making their workflow faster and more efficient.",
    "ground_truth_context": "\"\n\u201cFor 3D animators, there\u2019s nothing better than a GeForce RTX 4080 in combo with NVIDIA STUDIO drivers and future DLSS 3 support for Twinmotion, V-Ray, Unity, Cinema 4D, Arnold, Adobe Designer, 3D Painter and 3D Sampler.\u201d \u2014 Tuttotech.net\n\n\u201cAs far as I\u2019m concerned this thing is a no-brainer for anyone who does graphic intensive work, works in video production, or does high end streaming.\u201c \u2014 Jay Lippman\n\n\u201cOverall, the RTX 4080 16GB Founders Edition Graphics Card is an excellent choice for Content Creators and CG Artists who have been desperately looking for an upgrade over the past 2-3 years! For 3D GPU Rendering Workloads, in particular, we\u2019re happy to finally see a GPU that deserves a recommendation.\u201d \u2014 CG Director\n\n\u201cAs far as the 4080 goes for creative individuals, I\u2019ve got no doubt that if you\u2019re rendering 3D models or 4K video, you\u2019re going to have a fantastic time with this GPU. There\u2019s also now dual AV1 video encoders on board which means that you can stream at higher resolutions with the likes of Discord.\u201d \u2014 Press Start\n\nPick up the GeForce RTX 4080 GPU or a prebuilt system today using our Product Finder .\n\nConcept artist Pablo Mu\u00f1oz G\u00f3mez is equally passionate about helping digital artists \u2014 teaching 3D classes and running the ZBrush Guides website \u2014 as he is about his own creative specialties: concept and character artistry.\n\nHARVESTERS is a demo concept G\u00f3mez created to illustrate a complete ZBrush workflow for his students. He upgraded his render linework with color palette blocking and refinement, and finished with a Z-depth pass to create a depth-of-field effect.\n\nG\u00f3mez also excels in photorealistic 3D character modeling, as evidenced in his piece Tadpole .\n\nG\u00f3mez often uses Adobe Substance 3D Painter to apply colors and materials directly to his 3D models. NVIDIA Iray technology in the viewport enables G\u00f3mez to edit in real time and use ray-traced baking for faster rendering speeds \u2014 all accelerated by his hardware. Artists can expect even faster asset baking with GeForce RTX 40 Series GPUs.\n\nFor further customization, G\u00f3mez prefers to download assets from the vast Substance 3D Asset library and import into Substance 3D Sampler, adjusting a few sliders to create photorealistic materials. RTX-exclusive interactive ray tracing lets G\u00f3mez apply realistic effects in real time. Powered by GeForce RTX 40 Series GPUs, these tasks can be completed even faster than with the previous generation.\n\nWith GeForce RTX 40 Series GPUs, 3D artists like G\u00f3mez can now build scenes in fully ray-traced environments with accurate physics and realistic materials \u2014 all in real time, without proxies, in the NVIDIA Omniverse beta .\n\nDLSS 3 technology uses the AI-powered RTX Tensor Cores and a new Optical Flow Accelerator to generate additional frames and dramatically increase frames per second (FPS). This improves smoothness and speeds up movement in the viewport. NVIDIA is also working with popular 3D apps Unity and Unreal Engine to integrate DLSS 3.\""
  },
  {
    "question": "How are telcos using AI for internal operations?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDMvMTQvYWktZm9yLXRlbGVjb20tZ3RjLw==.pdf",
    "ground_truth_answer": "Telcos are using AI for internal operations such as analyzing terabytes of network data to detect anomalies, enhance security, and improve fraud detection, as well as for predictive maintenance to proactively identify and fix issues in hardware and software, and for virtual assistants in contact centers to enrich customer service and purchase experiences.",
    "ground_truth_context": "\"\nBig Leap in vRAN: Full-Stack Acceleration, Cloud-First, AI and 6G Ready\n\nBuilding and deploying 5G networks is costly. To monetize new infrastructure, telcos need to create new revenue opportunities with enterprise customers.\n\nPrivate 5G wireless solutions for industrial and factory applications have great monetization potential, with about half of telcos expecting 10% of enterprise revenue to come from private wireless by 2025.\n\nNVIDIA and Red Hat are making private networks cheaper to build and easier to scale with composable infrastructure that helps streamline use of resources.\n\nTo achieve this, Red Hat now supports NVIDIA converged accelerators and the NVIDIA Aerial software development kit for software-defined 5G vRAN and enterprise AI applications. The SDK simplifies building programmable and scalable 5G software, including edge and AI applications that are in demand with enterprise customers. With these capabilities, providers can unlock the full potential of 5G-driven use cases across hybrid and multi-cloud environments to deliver new services.\n\nHear how industry leaders are delivering enterprise edge AI at these GTC sessions:\n\nDelivering Enterprise AI Services on MEC: Three Perspectives From NTT Group\n\nUnlocking 5G\u2019s Potential at the Edge With State-of-the-Art NVIDIA GPUs\n\nAI is powering new offerings for customers, as well as underpinning efficiency gains for internal telecom operations and improved network service. In a recent NVIDIA survey , 60% of telcos said they were expecting to use AI automation to augment human-based operations. Technologies like avatars, generative AI and dynamic routing enable cost efficiencies.\n\nTo improve the quality of service, telcos are using AI to analyze terabytes of network data to detect anomalies, enhance security and improve fraud detection. AI-powered predictive maintenance is helping telcos proactively identify and fix issues in their hardware and software before performance is impacted.\n\nAdditionally, AI virtual assistants in contact centers are enriching customer service and purchase experiences while supporting human staff.\n\nLearn how AT&T; and Vodafone are using AI for telco operations at these GTC sessions:\n\nThe Future of Customer Service: How Speech AI Is Changing the Game\n\nOptimizing Fraud Detection Systems: The Case of Highly Imbalanced Data\n\nThe future of telecom networks and services will increasingly be based in the cloud and supported by accelerated computing and AI.\n\nFrom machine learning to edge computing and advanced software-defined architecture, NVIDIA is collaborating with partners on innovative technologies that will drive superior telecom performance.\n\nHear more about how NVIDIA and partners are building modern telco networks and a collaborative 5G ecosystem to transform services at GTC , and watch NVIDIA founder and CEO Jensen Huang\u2019s keynote address on Tuesday, March 21, at 8 a.m. PT.\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/03/14/ai-for-telecom-gtc/\""
  },
  {
    "question": "What is the challenge that Kirk Kaiser faced when building his self-driving skate park project?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDYvMTIva2lyay1rYWlzZXItamV0c29uLXNlbGYtZHJpdmluZy1za2F0ZS1wYXJrLw==.pdf",
    "ground_truth_answer": "Kirk Kaiser faced several challenges when building his self-driving skate park project, including the high cost of electrical components and the difficulty of getting a large platform to break along two axes of rotation. He overcame these challenges by scaling down the project to the size of a skateboard and using NVIDIA Jetson for the self-driving features.",
    "ground_truth_context": "\"\nHe was spurred to write the book while talking to high school students at a biohacker bootcamp in New York.\n\n\u201cWhat the high schoolers said blew my mind \u2014 they basically thought that software engineering was for overachievers,\u201d he said. \u201cSo I wanted to write a book that would convince younger people that programming is fundamentally a platform for creating worlds, and it can be for anyone, which is a really exciting thing.\u201d\n\nKaiser kicked off his self-driving skate park project 18 months ago, intending to start with a ramp about the size of a golf cart. The electrical components needed to steer it were prohibitively expensive, however, and getting such a large platform to break along two axes of rotation was incredibly challenging, he said.\n\nRescaling the project to the size of a skateboard itself, Kaiser bought a welder and a metal brake, learned how to use both tools for the first time, and built a platform that can raise and lower, as well as accept any kind of ramp.\n\nIt\u2019s fully steerable along both axes thanks to the edge capabilities of NVIDIA Jetson. And the developer\u2019s now training the platform\u2019s self-driving features using Robot Operating System repositories available through the NVIDIA Isaac platform for accelerated, AI-powered robotics.\n\n\u201cIn the machine learning space, NVIDIA is really the only show in town,\u201d he said. \u201cThe Jetson platform is the industry standard for edge AI, and its compatibility with other development platforms and the onboard GPU are huge pluses.\u201d\n\nKaiser dives deeper into the technical aspects of his skate ramp project on his blog .\n\nThe developer\u2019s other favorite projects using the NVIDIA Jetson platform include training an AI model for turning lights off and on using a dab and T-pose , as well as creating an AI-powered camera for bird-watching .\n\n\u201cThe acceleration of smaller-scale robotics is becoming more accessible to everyone,\u201d Kaiser said, \u201cwhich is really exciting because I think robotics is so damn cool.\u201d\n\nGo along for the ride by keeping up with Kaiser\u2019s work , and learn more about the NVIDIA Jetson platform .\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/06/12/kirk-kaiser-jetson-self-driving-skate-park/\""
  },
  {
    "question": "What is the name of Replit's coding AI?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDgvMTYvcmVwbGl0LWNlby1hbWphZC1tYXNhZC1vbi1lbXBvd2VyaW5nLXRoZS1uZXh0LWJpbGxpb24tc29mdHdhcmUtY3JlYXRvcnMv.pdf",
    "ground_truth_answer": "Replit's coding AI is called Ghostwriter.",
    "ground_truth_context": "\"\nReplit CEO Amjad Masad on Empowering the Next Billion Software Creators\n\nAuthor: Kristen Yee\n\nReplit aims to empower the next billion software creators.\n\nIn this week\u2019s episode of NVIDIA\u2019s AI Podcast , host Noah Kravitz dives into a conversation with Replit CEO Amjad Masad. Masad says the San Francisco-based maker of a software development platform, which came up as a member of NVIDIA\u2019s Inception program for startups, wants to bridge the gap between ideas and software, a task simplified by advances in generative AI.\n\n\u201cReplit is fundamentally about reducing the friction between an idea and a software product,\u201d Masad said.\n\nThe company\u2019s Ghostwriter coding AI has two main features: a code completion model and a chat model. These features not only make suggestions as users type their code, but also provide intelligent explanations of what a piece of code is doing, tracing dependencies and context. The model can even flag errors and offer solutions \u2014 like a full collaborator in a Google Docs for code.\n\nThe company is also developing \u201cmake me an app\u201d functionality. This tool allows users to provide high-level instructions to an Artificial Developer Intelligence, which then builds, tests and iterates the requested software.\n\nThe aim is to make software creation accessible to all, even those with no coding experience. While this feature is still under development, Masad said the company plans to improve it over the next year, potentially having it ready for developers in the next six to eight months.\n\nGoing forward, Masad envisions a future where AI functions as a collaborator, able to conduct high-level tasks and even manage resources. \u201cWe\u2019re entering a period where software is going to feel more alive,\u201d Masad said. \u201cAnd so I think computing is becoming more humane, more accessible, more exciting, more natural.\u201d <\n\nh2>You Might Also Like\n\nJules Anh Tuan Nguyen Explains How AI Lets Amputee Control Prosthetic Hand, Video Games A postdoctoral researcher at the University of Minnesota discusses his efforts to allow amputees to control their prosthetic limb \u2014 right down to the finger motions \u2014 with their minds.\n\nOverjet\u2019s Ai Wardah Inam on Bringing AI to Dentistry Overjet, a member of NVIDIA Inception , is moving fast to bring AI to dentists\u2019 offices. Dr. Wardah Inam, CEO of the company, discusses using AI to improve patient care.\n\nImmunai CTO and Co-Founder Luis Voloch on Using Deep Learning to Develop New Drugs Luis Voloch, co-founder and chief technology officer of Immunai, talks about tackling the challenges of the immune system with a machine learning and data science mindset.\n\nIn addition to Amazon Music , get the AI Podcast through iTunes , Google Podcasts , Google Play , Castbox , DoggCatcher, Overcast , PlayerFM , Pocket Casts, Podbay , PodBean , PodCruncher, PodKicker, Soundcloud , Spotify , Stitcher and TuneIn .\n\nMake the AI Podcast better. Have a few minutes to spare? Fill out this listener survey .\""
  },
  {
    "question": "How can generative AI be used to tackle global challenges?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDkvMTMvYW5pbWEtYW5hbmRrdW1hci1nZW5lcmF0aXZlLWFpLw==.pdf",
    "ground_truth_answer": "Generative AI can be used to predict dangerous coronavirus variants, accelerate drug and vaccine research, and predict extreme weather events like hurricanes or heat waves. It can also be used to understand the language of genomes and craft a model that can help with drug development and extreme weather prediction.",
    "ground_truth_context": "\"\nUnlocking the Language of Genomes and Climates: Anima Anandkumar on Using Generative AI to Tackle Global Challenges Top NVIDIA researcher speaks on generative AI providing opportunities to get ahead of the curve on challenges like drug development and extreme weather.\n\nAuthor: Kristen Yee\n\nGenerative AI-based models can not only learn and understand natural languages \u2014 they can learn the very language of nature itself, presenting new possibilities for scientific research.\n\nAnima Anandkumar, Bren Professor at Caltech and senior director of AI research at NVIDIA, was recently invited to speak at the President\u2019s Council of Advisors on Science and Technology .\n\nAt the talk, Anandkumar said that generative AI was described as \u201can inflection point in our lives,\u201d with discussions swirling around how to \u201charness it to benefit society and humanity through scientific applications.\u201d\n\nOn the latest episode of NVIDIA\u2019s AI Podcast , host Noah Kravitz spoke with Anandkumar on generative AI\u2019s potential to make splashes in the scientific community.\n\nIt can, for example, be fed DNA, RNA, viral and bacterial data to craft a model that understands the language of genomes. That model can help predict dangerous coronavirus variants to accelerate drug and vaccine research.\n\nGenerative AI can also predict extreme weather events like hurricanes or heat waves. Even with an AI boost, trying to predict natural events is challenging because of the sheer number of variables and unknowns.\n\n\u201cThose are the aspects we\u2019re working on at NVIDIA and Caltech, in collaboration with many other organizations, to say, \u2018How do we capture the multitude of scales present in the natural world?\u2019\u201d she said. \u201cWith the limited data we have, can we hope to extrapolate to finer scales? Can we hope to embed the right constraints and come up with physically valid predictions that make a big impact?\u201d\n\nAnandkumar adds that to ensure AI models are responsibly and safely used, existing laws must be strengthened to prevent dangerous downstream applications.\n\nShe also talks about the AI boom, which is transforming the role of humans across industries, and problems yet to be solved.\n\n\u201cThis is the research advice I give to everyone: the most important thing is the question, not the answer,\u201d she said.\n\nJules Anh Tuan Nguyen Explains How AI Lets Amputee Control Prosthetic Hand, Video Games A postdoctoral researcher at the University of Minnesota discusses his efforts to allow amputees to control their prosthetic limb \u2014 right down to the finger motions \u2014 with their minds.\n\nOverjet\u2019s Ai Wardah Inam on Bringing AI to Dentistry Overjet, a member of NVIDIA Inception , is moving fast to bring AI to dentists\u2019 offices. Dr. Wardah Inam, CEO of the company, discusses using AI to improve patient care.\n\nImmunai CTO and Co-Founder Luis Voloch on Using Deep Learning to Develop New Drugs Luis Voloch talks about tackling the challenges of the immune system with a machine learning and data science mindset.\""
  },
  {
    "question": "What is the main idea of the first paper discussed in the passage?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDUvMDIvZ3JhcGhpY3MtcmVzZWFyY2gtYWR2YW5jZXMtZ2VuZXJhdGl2ZS1haS1uZXh0LWZyb250aWVyLw==.pdf",
    "ground_truth_answer": "The first paper discusses a technique that can customize the output of a machine learning model using a single example image, accelerating the personalization process from minutes to roughly 11 seconds on a single NVIDIA A100 Tensor Core GPU, more than 60x faster than previous personalization approaches.",
    "ground_truth_context": "\"\nOne paper describes a technique that needs a single example image to customize its output, accelerating the personalization process from minutes to roughly 11 seconds on a single NVIDIA A100 Tensor Core GPU , more than 60x faster than previous personalization approaches.\n\nA second paper introduces a highly compact model called Perfusion, which takes a handful of concept images to allow users to combine multiple personalized elements \u2014 such as a specific teddy bear and teapot \u2014 into a single AI-generated visual:\n\nOnce a creator comes up with concept art for a virtual world, the next step is to render the environment and populate it with 3D objects and characters. NVIDIA Research is inventing AI techniques to accelerate this time-consuming process by automatically transforming 2D images and videos into 3D\n\nrepresentations that creators can import into graphics applications for further editing.\n\nA third paper created with researchers at the University of California, San Diego, discusses tech that can generate and render a photorealistic 3D head-and-shoulders model based on a single 2D portrait \u2014 a major breakthrough that makes 3D avatar creation and 3D video conferencing accessible with AI. The method runs in real time on a consumer desktop, and can generate a photorealistic or stylized 3D telepresence using only conventional webcams or smartphone cameras.\n\nA fourth project, a collaboration with Stanford University, brings lifelike motion to 3D characters. The researchers created an AI system that can learn a range of tennis skills from 2D video recordings of real tennis matches and apply this motion to 3D characters . The simulated tennis players can accurately hit the ball to target positions on a virtual court, and even play extended rallies with other characters.\n\nBeyond the test case of tennis, this SIGGRAPH paper addresses the difficult challenge of producing 3D characters that can perform diverse skills with realistic movement \u2014 without the use of expensive motion-capture data.\n\nOnce a 3D character is generated, artists can layer in realistic details such as hair \u2014 a complex, computationally expensive challenge for animators.\n\nHumans have an average of 100,000 hairs on their heads, with each reacting dynamically to an individual\u2019s motion and the surrounding environment. Traditionally, creators have used physics formulas to calculate hair movement, simplifying or approximating its motion based on the resources available. That\u2019s why virtual characters in a big-budget film sport much more detailed heads of hair than real-time video game avatars.\n\nA fifth paper showcases a method that can simulate tens of thousands of hairs in high resolution and in real time using neural physics, an AI technique that teaches a neural network to predict how an object would move in the real world.\""
  },
  {
    "question": "What is the name of the new P5 instances that NVIDIA and AWS have collaborated on?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDcvMjYvYXdzLWNsb3VkLWgxMDAv.pdf",
    "ground_truth_answer": "The new P5 instances are called Amazon EC2 P5 instances featuring NVIDIA H100 GPUs.",
    "ground_truth_context": "\"\nNVIDIA and AWS have collaborated for more than a dozen years to bring GPU acceleration to the cloud. The new P5 instances, the latest example of that collaboration, represents a major step forward to deliver the cutting-edge performance that enables developers to invent the next generation of AI.\n\nHere are some examples of what customers are already saying:\n\nAnthropic builds reliable, interpretable and steerable AI systems that will have many opportunities to create value commercially and for public benefit.\n\n\u201cWhile the large, general AI systems of today can have significant benefits, they can also be unpredictable, unreliable and opaque, so our goal is to make progress on these issues and deploy systems that people find useful,\u201d said Tom Brown, co-founder of Anthropic. \u201cWe expect P5 instances to deliver substantial price-performance benefits over P4d instances, and they\u2019ll be available at the massive scale required for building next-generation LLMs and related products.\u201d\n\nCohere, a leading pioneer in language AI, empowers every developer and enterprise to build products with world-leading natural language processing (NLP) technology while keeping their data private and secure.\n\n\u201cCohere leads the charge in helping every enterprise harness the power of language AI to explore, generate, search for and act upon information in a natural and intuitive manner, deploying across multiple cloud platforms in the data environment that works best for each customer,\u201d said Aidan Gomez, CEO of Cohere. \u201cNVIDIA H100-powered Amazon EC2 P5 instances will unleash the ability of businesses to create, grow and scale faster with its computing power combined with Cohere\u2019s state-of-the-art LLM and generative AI capabilities.\u201d\n\nFor its part, Hugging Face is on a mission to democratize good machine learning.\n\n\u201cAs the fastest growing open-source community for machine learning, we now provide over 150,000 pretrained models and 25,000 datasets on our platform for NLP, computer vision, biology, reinforcement learning and more,\u201d said Julien Chaumond, chief technology officer and co-founder of Hugging Face. \u201cWe\u2019re looking forward to using Amazon EC2 P5 instances via Amazon SageMaker at scale in UltraClusters with EFA to accelerate the delivery of new foundation AI models for everyone.\u201d\n\nToday, more than 450 million people around the world use Pinterest as a visual inspiration platform to shop for products personalized to their taste, find ideas and discover inspiring creators.\n\n\u201cWe use deep learning extensively across our platform for use cases such as labeling and categorizing billions of photos that are uploaded to our platform, and visual search that provides our users the ability to go from inspiration to action,\u201d said David Chaiken, chief architect at Pinterest. \u201cWe\u2019re looking forward to using Amazon EC2 P5 instances featuring NVIDIA H100 GPUs, AWS EFA and UltraClusters to accelerate our product development and bring new empathetic AI-based experiences to our customers.\u201d\""
  },
  {
    "question": "What is the benefit of using NVIDIA Maxine's cloud-native microservices?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDkvMjAvbWF4aW5lLWNsb3VkLW5hdGl2ZS8=.pdf",
    "ground_truth_answer": "Maxine's cloud-native microservices allow developers to build real-time AI applications. Microservices can be independently managed and deployed seamlessly in the cloud, accelerating development timelines.",
    "ground_truth_context": "\"\nNew NVIDIA Maxine Cloud-Native Architecture Delivers Breakthrough Audio and Video Quality at Scale\n\nEarly-access AI microservices deliver premium-quality communications in the cloud.\n\nAuthor: Delilah Liu\n\nThe latest release of NVIDIA Maxine is paving the way for real-time audio and video communications. Whether for a video conference, a call made to a customer service center, or a live stream, Maxine enables clear communications to enhance virtual interactions.\n\nNVIDIA Maxine is a suite of GPU-accelerated AI software development kits (SDKs) and cloud-native microservices for deploying optimized and accelerated AI features that enhance audio, video and augmented-reality (AR) effects in real time.\n\nAnd with Maxine\u2019s state-of-the-art models, end users don\u2019t need expensive gear to improve audio and video. Using NVIDIA AI-based technology, these high-quality effects can be achieved with standard microphones and camera equipment.\n\nAt GTC , NVIDIA announced the re-architecture of Maxine for cloud-native microservices, with the early-access release of Maxine\u2019s audio-effects microservice. Additionally, new Maxine SDK features were unveiled, including Speaker Focus and Face Expression Estimation, as well as the general availability of Eye Contact. NVIDIA Maxine now also includes enhanced versions of existing SDK features.\n\nMaxine\u2019s cloud-native microservices allow developers to build real-time AI applications. Microservices can be independently managed and deployed seamlessly in the cloud, accelerating development timelines.\n\nThe Audio Effects microservice, available in early access, contains four state-of-the-art audio features:\n\nBackground Noise Removal: Removes several common background noises using AI models, while preserving the speaker\u2019s natural voice.\n\nRoom Echo Removal : Removes reverberations from audio using AI models, restoring clarity of a speaker\u2019s voice.\n\nAudio Super Resolution: Improves audio quality by increasing the temporal resolution of audio signal. It currently supports upsampling from 8 kHz to 16 kHz and from 16 kHz to 48 kHz.\n\nAcoustic Echo Cancellation: Cancels real-time acoustic device echo from the input-audio stream, eliminating mismatched acoustic pairs and double-talk. With AI-based technology, more effective cancellation is achieved than with traditional digital signal processing.\n\nPexip , a leading provider of enterprise video conferencing and collaboration solutions, is using NVIDIA AI technologies to take virtual meetings to the next level with advanced features for the modern workforce.\n\n\u201cWith Maxine\u2019s move to cloud-native microservices, it will be even easier to combine NVIDIA\u2019s advanced AI technologies with our own unique server-side architecture,\u201d said Eddie Clifton, senior vice president of Strategic Alliances at Pexip. \u201cThis allows our teams at Pexip to deliver an enhanced experience for virtual meetings.\u201d\n\nSign up for early access .\""
  },
  {
    "question": "How can WPP publish 3D experiences to the web with ease?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDgvMDgvZGVuemEtd3BwLWNhci1jb25maWd1cmF0b3JzLW52aWRpYS1vbW5pdmVyc2UtY2xvdWQv.pdf",
    "ground_truth_answer": "WPP can publish 3D experiences to the web with ease by using NVIDIA Omniverse Cloud and Graphics Delivery Network (GDN), which allows for real-time, high-fidelity 3D content to be served to nearly any web device with just one click.",
    "ground_truth_context": "\"\nOnce the 3D experience is complete, with just one click, WPP can publish it to Graphics Delivery Network (GDN) , part of NVIDIA Omniverse Cloud . GDN is a network of data centers built to serve real-time, high-fidelity 3D content to nearly any web device, enabling interactive experiences in the dealer showroom as well as on consumers\u2019 mobile devices.\n\nThis eliminates the tedious process of manually packaging, deploying, hosting and managing the experience themselves. If updates are needed, just like with the initial deployment, WPP can publish them with a single click.\n\nCTA: Learn more about Omniverse Cloud and GDN .\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/08/08/denza-wpp-car-configurators-nvidia-omniverse-cloud/\""
  },
  {
    "question": "What tool did Abbitt use for sculpting and retopologizing his 3D model?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDUvMDIvYmxlbmRlci1vcHRpeC1haS8=.pdf",
    "ground_truth_answer": "Abbitt used Blender for sculpting and retopologizing his 3D model.",
    "ground_truth_context": "\"\nHe began with the initial blockout, a 3D rough-draft level built using simple 3D shapes without details or polished art assets. The goal of the blockout was to prototype, test and adjust the foundational shapes of the dragon. Abbitt then combined block shapes into a single mesh model, the structural build of a 3D model, consisting of polygons.\n\nMore sculpting was followed by retopologizing the mesh, the process of simplifying the topology of a mesh to make it cleaner and easier to work with. This is a necessary step for images that will undergo more advanced editing and distortions.\n\nAdding Blender\u2019s multiresolution modifier enabled Abbitt to subdivide a mesh, especially useful for re-projecting details from another sculpt with a Shrinkwrap modifier, which allows an object to \u201cshrink\u201d to the surface of another object. It can be applied to meshes, lattices, curves, surfaces and texts.\n\nAt this stage, the power of Abbitt\u2019s GeForce RTX 4090 GPU really started to shine. He sculpted fine details faster with Blender Cycles RTX-accelerated OptiX ray tracing in the viewport for fluid, interactive modeling with photorealistic detail. Baking and applying textures were done with buttery smooth ease.\n\nThe RTX 4090 GPU also accelerated the animation phase, where the artist rigged and posed his model. \u201cModern content creators require GPU technology to see their creative visions fully realized at an efficient pace,\u201d Abbitt said.\n\nFor the texturing, painting and rendering process, Abbitt said he found it \u201cextremely useful to be able to see the finished results without a huge render time, thanks to NVIDIA OptiX.\u201d\n\nRendering final files in popular 3D creative apps \u2014 like Blender, Autodesk Maya with Autodesk Arnold, OTOY\u2019s OctaneRender and Maxon\u2019s Redshift \u2014 is made 70-200% faster with an RTX 4090 GPU, compared to previous-generation cards. This results in invaluable time saved for a freelancer with a deadline or a student working on a group project.\n\nAbbitt\u2019s RTX GPU enabled OptiX ray tracing in Blender Cycles for the fastest final frame render.\n\n\u201cNVIDIA GeForce RTX graphics cards are really the only choice at the moment for Blender users, because they offer so much more speed during render times,\u201d said Abbitt. \u201cYou can quickly see results and make the necessary changes.\u201d\n\nCheck out Abbitt\u2019s YouTube channel with livestreams every Friday at 9 a.m. PT.\n\nFollow NVIDIA Studio on Instagram , Twitter and Facebook . Access tutorials on the Studio YouTube channel and get updates directly in your inbox by subscribing to the Studio newsletter .\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/05/02/blender-optix-ai/\""
  },
  {
    "question": "What is the name of the artist who created Natural Coffee?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDgvMDgvc2lnZ3JhcGgtc3R1ZGlvLXJ0eC1vbW5pdmVyc2Utb3BlbnVzZC8=.pdf",
    "ground_truth_answer": "Andrew Averkin",
    "ground_truth_context": "\"\nWords can\u2019t espresso the stunning 3D scene Natural Coffee .\n\nNVIDIA artist Andrew Averkin has over 15 years of experience in the creative field. He finds joy in a continuous journey \u2014 blending art and technology \u2014 to bring his vivid imagination to life.\n\nHis work, Natural Coffee , has a compelling origin story. Once upon a time, in a bustling office, there was a cup of \u201cnatural coffee\u201d known for its legendary powers. It gave artists nerves of steel at work, improved performance across the board and, as a small bonus, offered magical music therapy.\n\nAverkin used an image generator to quickly cycle through visual ideas created from simple text-based prompts. Using AI to brainstorm imagery at the beginning of creative workflows is becoming more popular by artists looking to save time on iteration.\n\nWith a visual foundation, Averkin speeds up the process by acquiring 3D assets from online stores to quickly build a 3D blockout of the scene, a rough-draft level built using simple 3D shapes without details or polished details.\n\nNext, Averkin polished individual assets in Autodesk 3ds Max, sculpting models with fine detail, testing and applying different textures and materials. His GeForce RTX 4090 GPU unlocked RTX-accelerated AI denoising \u2014 with the default Autodesk Arnold renderer \u2014 delivering interactive 3D modeling, which helped tremendously while composing the scene.\n\n\u201cI chose a GeForce RTX graphics card for quality, speed and safety, plain and simple,\u201d said Averkin.\n\nAverkin then exported Natural Coffee to the NVIDIA Omniverse USD Composer app via the Autodesk 3ds Max Connector. \u201cInside USD Composer I added more details, played a lot with a built-in collection of materials, plus did a lot of lighting work to make composition look more realistic,\u201d he explained.\n\nOne of the biggest benefits in USD Composer is the ability to review scenes rendering in real time with photorealistic light, shadows, textures and more. This dramatically improves the process of editing massive 3D scenes, making it quicker and easier. Averkin was even able to add a camera fly animation, further elevating the scene.\n\nThe final step was to add a few touch-ups in Adobe Photoshop. Over 30 GPU-accelerated features gave Averkin plenty of options for playing with colors and contrast, and making final image adjustments smoothly and quickly.\n\nAverkin encourages advanced 3D artists to experiment with the OpenUSD framework. \u201cI use it a lot in my work at NVIDIA and in personal projects,\u201d he said. \u201cOpenUSD is very powerful. It helps with work in multiple creative apps in a non-destructive way, and other great features make the entire process easier and more flexible.\u201d\n\nCheck out Averkin\u2019s portfolio on ArtStation .\n\nFollow NVIDIA Studio on Instagram , Twitter and Facebook . Access tutorials on the Studio YouTube channel and get updates directly in your inbox by subscribing to the Studio newsletter .\""
  },
  {
    "question": "How could AI enhance patient care in the future?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDYvMjIvZGVsaXJpdW0tZGV0ZWN0aW9uLWFpLw==.pdf",
    "ground_truth_answer": "AI has the potential to revolutionize critical care by enabling early intervention and forecasting conditions like dementia.",
    "ground_truth_context": "\"\nThe research presents a promising method for delirium detection that could shorten hospital stays, increase discharge rates, decrease mortality rates and reduce the financial burden associated with delirium.\n\nBy integrating the power of NVIDIA GPUs with innovative deep learning models and practical medical devices, this study underlines the transformative potential of technology in enhancing patient care.\n\nAs AI grows and develops, medical professionals are increasingly likely to rely on it to forecast conditions like dementia and intervene early, revolutionizing the future of critical care.\n\nRead the full paper .\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/06/22/delirium-detection-ai/\""
  },
  {
    "question": "What is the name of Juliestrator's five-part tutorial series on building 3D worlds?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTEvMDgvaW4tdGhlLW52aWRpYS1zdHVkaW8tbm92ZW1iZXItMDgv.pdf",
    "ground_truth_answer": "Modeling 3D New York Diorama",
    "ground_truth_context": "\"\nThough she enjoys the modeling stage, Juliestrator said that the desire to refine an endless number of details can be overwhelming. As such, she deploys an \u201c80/20 rule,\u201d dedicating no more than 20% of the entire project\u2019s timeline to detailed modeling. \u201cThat\u2019s the magic of the 80/20 rule: tackle the correct 20%, and the other 80% often falls into place,\u201d she said.\n\nJuliestrator finally adjusts the composition in 3D \u2014 manipulating the light objects, rotating the camera and adding animations. She completed all of this quickly with an assist from RTX-accelerated OptiX ray tracing in the Blender viewport, using Blender Cycles for the fastest frame renders.\n\nBlender is Juliestrator\u2019s preferred 3D modeling app, she said, due to its ease of use and powerful AI features, as well as its accessibility. \u201cI truly appreciate the efforts of the Blender Foundation and all of its partners in keeping Blender free and available to people from all over the world, to enhance anyone\u2019s creativity,\u201d she said.\n\nJuliestrator chose to use an NVIDIA Studio laptop, a \u201cporta-bella\u201d system for efficiency and convenience, she said. \u201cI needed a powerful computer that would let me use both Blender and a game engine like Unity or Unreal Engine 5, while staying mobile and on the go,\u201d the artist added.\n\nCheck out Juliestrator\u2019s portfolio and social media links .\n\nFor more direction and inspiration for building 3D worlds, check out Juliestrator\u2019s five-part tutorial, Modeling 3D New York Diorama , which covers the critical stages in 3D workflows: sketching composition , modeling details and more. The tutorials can be found on the NVIDIA Studio YouTube channel , which posts new videos every week.\n\nAnd don\u2019t forget to enter the NVIDIA Studio #WinterArtChallenge on Instagram , Twitter or Facebook .\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/11/08/in-the-nvidia-studio-november-08/\""
  },
  {
    "question": "What is the name of the studio that created Roving Romanesco?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDIvMjgvaW4tdGhlLW52aWRpYS1zdHVkaW8tZmVicnVhcnktMjgv.pdf",
    "ground_truth_answer": "ManvsMachine",
    "ground_truth_context": "\"\nMany advanced nodes in Nuke are GPU accelerated, which gave the team another speed advantage.\n\nProjects like Roving Romanesco represent the high-quality work ManvsMachine strives to deliver for clients.\n\n\u201cOur ethos is reflected in our name,\u201d said ManvsMachine. \u201cEqual importance is placed on ideas and execution. Rather than sell an idea and then work out how to make it later, the preference is to present clients with the full picture, often leading with technique to inform the creative.\u201d\n\nCheck out @man.vs.machine on Instagram for more inspirational work.\n\nArtists looking to hone their Houdini skills can access Studio Shortcuts and Sessions on the NVIDIA Studio YouTube channel . Discover exclusive step-by-step tutorials from industry-leading artists, watch inspiring community showcases and more, powered by NVIDIA Studio hardware and software .\n\nFollow NVIDIA Studio on Instagram , Twitter and Facebook . Access tutorials on the Studio YouTube channel and get updates directly in your inbox by subscribing to the Studio newsletter .\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/02/28/in-the-nvidia-studio-february-28/\""
  },
  {
    "question": "Which companies are adopting NVIDIA MGX?",
    "document": "TlZJRElBIE1HWCA1LzI4LzIzLnBkZg==.pdf",
    "ground_truth_answer": "ASRock Rack, ASUS, GIGABYTE, Pegatron, QCT and Supermicro will adopt MGX.",
    "ground_truth_context": "\"\nNVIDIA MGX Gives System Makers Modular Architecture to Meet Diverse Accelerated Computing Needs of World\u2019s Data Centers\n\nQCT and Supermicro Among First to Use Server Spec Enabling 100+ System Configurations to Accelerate AI, HPC, Omniverse Workloads\n\nCOMPUTEX\u2014To meet the diverse accelerated computing needs of the world\u2019s data centers, NVIDIA today unveiled the NVIDIA MGX\u2122 server specification, which provides system manufacturers with a modular reference architecture to quickly and cost-effectively build more than 100 server variations to suit a wide range of AI, high performance computing and Omniverse applications.\n\nASRock Rack, ASUS, GIGABYTE, Pegatron, QCT and Supermicro will adopt MGX, which can slash development costs by up to three-quarters and reduce development time by two-thirds to just six months.\n\n\u201cEnterprises are seeking more accelerated computing options when architecting data centers that meet their specific business and application needs,\u201d said Kaustubh Sanghani, vice president of GPU products at NVIDIA. \u201cWe created MGX to help organizations bootstrap enterprise AI, while saving them significant amounts of time and money.\u201d\n\nWith MGX, manufacturers start with a basic system architecture optimized for accelerated computing for their server chassis, and then select their GPU, DPU and CPU. Design variations can address unique workloads, such as HPC, data science, large language models, edge computing, graphics and video, enterprise AI, and design and simulation. Multiple tasks like AI training and 5G can be handled on a single machine, while upgrades to future hardware generations can be frictionless. MGX can also be easily integrated into cloud and enterprise data centers.\n\nCollaboration With Industry Leaders QCT and Supermicro will be the first to market, with MGX designs appearing in August. Supermicro\u2019s ARS-221GL-NR system, announced today, will include the NVIDIA Grace\u2122 CPU Superchip, while QCT\u2019s S74G-2U system, also announced today, will use the NVIDIA GH200 Grace Hopper Superchip.\n\nAdditionally, SoftBank Corp. plans to roll out multiple hyperscale data centers across Japan and use MGX to dynamically allocate GPU resources between generative AI and 5G applications.\n\n\u201cAs generative AI permeates across business and consumer lifestyles, building the right infrastructure for the right cost is one of network operators\u2019 greatest challenges,\u201d said Junichi Miyakawa, president and CEO at SoftBank Corp. \u201cWe expect that NVIDIA MGX can tackle such challenges and allow for multi-use AI, 5G and more depending on real-time workload requirements.\u201d\n\nDifferent Designs for Different Needs Data centers increasingly need to meet requirements for both growing compute capabilities and decreasing carbon emissions to combat climate change, while also keeping costs down.\""
  },
  {
    "question": "Which companies will offer custom boards for the RTX 4060 family?",
    "document": "R2VGb3JjZSBSVFggNDA2MCBGYW1pbHkgNS8xOC8yMy5wZGY=.pdf",
    "ground_truth_answer": "ASUS, Colorful, Gainward, GALAX, GIGABYTE, INNO3D, KFA2, MSI, Palit, PNY, and ZOTAC will offer custom boards for the RTX 4060 family, including stock-clocked and factory-overclocked models.",
    "ground_truth_context": "\"\nAn NVIDIA Founders Edition design of the GeForce RTX 4060 Ti 8GB will be available directly from NVIDIA.com and select retailers. Custom boards for the entire RTX 4060 family, including stock-clocked and factory-overclocked models, will be available from top add-in card providers such as ASUS, Colorful, Gainward, GALAX, GIGABYTE, INNO3D, KFA2, MSI, Palit, PNY and ZOTAC, as well as from gaming system integrators and builders worldwide.\n\nAbout NVIDIA Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company\u2019s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the industrial metaverse. NVIDIA is now a full-stack computing company with data- center-scale offerings that are reshaping industry. More information at https://nvidianews.nvidia.com/.\""
  },
  {
    "question": "What is BioNeMo?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDMvMjEvZ3RjLWtleW5vdGUtc3ByaW5nLTIwMjMv.pdf",
    "ground_truth_answer": "BioNeMo is a platform for creating, fine-tuning, and serving custom AI models for drug discovery and other healthcare applications.",
    "ground_truth_context": "\"\nAnd NVIDIA announced Amgen is accelerating drug discovery services with BioNeMo. In addition, Alchemab Therapeutics, AstraZeneca, Evozyne, Innophore and Insilico are all early access users of BioNemo.\n\nBioNeMo helps researchers create, fine-tune and serve custom models with their proprietary data, Huang explained.\n\nHuang also announced that NVIDIA and Medtronic , the world\u2019s largest healthcare technology provider, are partnering to build an AI platform for software-defined medical devices. The partnership will create a common platform for Medtronic systems, ranging from surgical navigation to robotic-assisted surgery.\n\nAnd today Medtronic announced that its GI Genius system, with AI for early detection of colon cancer, is built on NVIDIA Holoscan, a software library for real-time sensor processing systems, and will ship around the end of this year.\n\n\u201cThe world\u2019s $250 billion medical instruments market is being transformed,\u201d Huang said.\n\nTo help companies deploy rapidly emerging generative AI models, Huang announced inference platforms for AI video, image generation, LLM deployment and recommender inference . They combine NVIDIA\u2019s full stack of inference software with the latest NVIDIA Ada, Hopper and Grace Hopper processors \u2014 including the NVIDIA L4 Tensor Core GPU and the NVIDIA H100 NVL GPU , both launched today.\n\n(cid:127) NVIDIA L4 for AI Video can deliver 120x more AI-powered video performance than CPUs, combined with 99% better energy efficiency.\n\n(cid:127) NVIDIA L40 for Image Generation is optimized for graphics and AI-enabled 2D, video and 3D image generation.\n\n(cid:127) NVIDIA H100 NVL for Large Language Model Deployment is ideal for deploying massive LLMs like ChatGPT at scale.\n\n(cid:127) And NVIDIA Grace Hopper for Recommendation Models is ideal for graph recommendation models, vector databases and graph neural networks.\n\nGoogle Cloud is the first cloud service provider to offer L4 to customers with the launch of its new G2 virtual machines, available in private preview today. Google is also integrating L4 into its Vertex AI model store.\n\nUnveiling a second cloud service to speed unprecedented simulation and collaboration capabilities to enterprises, Huang announced NVIDIA is partnering with Microsoft to bring NVIDIA Omniverse Cloud, a fully managed cloud service, to the world\u2019s industries .\n\n\u201cMicrosoft and NVIDIA are bringing Omniverse to hundreds of millions of Microsoft 365 and Azure users,\u201d Huang said, also unveiling new NVIDIA OVX servers and a new generation of workstations powered by NVIDIA RTX Ada Generation GPUs and Intel\u2019s newest CPUs optimized for NVIDIA Omniverse .\n\nTo show the extraordinary capabilities of Omniverse, NVIDIA\u2019s open platform built for 3D design collaboration and digital twin simulation, Huang shared a video showing how NVIDIA Isaac Sim, NVIDIA\u2019s robotics simulation and synthetic generation platform, built on Omniverse, is helping Amazon save time and money with full-fidelity digital twins.\""
  },
  {
    "question": "What is the name of the game that was originally announced in October but has a release date of Monday, Nov. 7?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTEvMDMvZ2Vmb3JjZS1ub3ctdGh1cnNkYXktbm92LTMv.pdf",
    "ground_truth_answer": "The Unliving",
    "ground_truth_context": "\"\nFilament (Free on Epic Games , Nov. 3-10)\n\nSTAR OCEAN THE DIVINE FORCE ( Steam )\n\nPAGUI ( Steam )\n\nRISK: Global Domination ( Steam )\n\nTotal War: THREE KINGDOMS ( Steam )\n\nBut wait, there\u2019s more! Among the total 26 games joining GeForce NOW in November is the highly anticipated Warhammer 40,000: Darktide , with support for NVIDIA RTX and DLSS .\n\nHere\u2019s a sneak peak:\n\nThe Unliving (New release on Steam , Nov. 7)\n\nTERRACOTTA (New release on Steam and Epic Games , Nov. 7)\n\nA Little to the Left (New Release on Steam , Nov. 8)\n\nYum Yum Cookstar (New Release on Steam , Nov. 11)\n\nNobody \u2014 The Turnaround (New release on Steam , Nov. 17)\n\nGoat Simulator 3 (New release on Epic Games, Nov. 17)\n\nEvil West (New release on Steam , Nov. 22)\n\nColortone: Remixed (New Release on Steam , Nov. 30)\n\nWarhammer 40,000: Darktide (New Release on Steam , Nov. 30)\n\nHeads Will Roll: Downfall ( Steam )\n\nGuns Gore and Cannoli 2 ( Steam )\n\nHidden Through TIme ( Steam )\n\nCave Blazers ( Steam )\n\nRailgrade ( Epic Games )\n\nThe Legend of Tianding ( Steam )\n\nWhile The Unliving was originally announced in October, the release date of the game shifted to Monday, Nov. 7.\n\nOctober brought more treats for members. Don\u2019t miss the 14 extra titles added last month.\n\nLEGO Bricktales ( Epic Games )\n\nRabbids: Party of Legends Ubisoft )\n\nThe Darkest Tales ( Steam )\n\nDual Universe ( Steam )\n\nBatora \u2014 Lost Haven ( Steam )\n\nWarhammer 40,000: Shootas, Blood & Teef ( Epic Games )\n\nThe Tenants ( Steam )\n\nEvoland Legendary Edition ( Epic Games )\n\nPaper Cut Mansion ( Steam and Epic Games )\n\nSaturnalia ( Epic Games )\n\nAsterigos: Curse of the Stars ( Epic Games )\n\nFive Nights at Freddy\u2019s: Security Breach ( Steam and Epic Games )\n\nSniper Elite 5 ( Steam )\n\nV Rising ( Steam )\n\nWith all of these sweet new titles coming to the cloud, getting your game on is as easy as pie. Speaking of pie, we\u2019ve got a question for you. Let us know your answer on Twitter or in the comments below. If GFN were a pie, what pie would it be? n \u2014 nn NVIDIA GeForce NOW (@NVIDIAGFN) November 2, 2022\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/11/03/geforce-now-thursday-nov-3/\""
  },
  {
    "question": "What is the goal of using AI in heavy-vehicle industry in Australia?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTAvMjQvc2Vuc2VuLWluc3BlY3RzLXRydWNrcy13aXRoLWFpLw==.pdf",
    "ground_truth_answer": "The goal is to waste less time tracking repeat compliant vehicles, present clearer information on vehicles and loads, and use vehicles as a mobile intelligence tool.",
    "ground_truth_context": "\"\n\u201cUsing this solution to obtain real-time heavy vehicle sightings from any location in Australia allows us to further digitize our operations and create a more efficient and safer heavy-vehicle industry in Australia,\u201d said Paul Simionato, director of the southern region at NHVR.\n\nThe ultimate goal: waste less time tracking repeat compliant vehicles, present clearer information on vehicles and loads, and use vehicles as a mobile intelligence tool.\n\nAnd perhaps best of all, operators who are consistently compliant can expect to be less regularly intercepted, creating a strong incentive for the industry to increase compliance.\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/10/24/sensen-inspects-trucks-with-ai/\""
  },
  {
    "question": "What is the name of the extension of the Omniverse platform that enables developers to generate labeled synthetic data?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDYvMTMvcmVuZGVyZWQtYWktb21uaXZlcnNlLXJlcGxpY2F0b3ItaW50ZWdyYXRpb24v.pdf",
    "ground_truth_answer": "Omniverse Replicator",
    "ground_truth_context": "\"\nRendered.ai Integrates NVIDIA Omniverse for Synthetic Data Generation NVIDIA Inception member Rendered.ai makes AI training simpler and more accessible with synthetic data generation platform integrating Omniverse Replicator.\n\nAuthor: Katja Reitemeyer\n\nRendered.ai is easing AI training for developers, data scientists and others with its platform-as-a-service for synthetic data generation , or SDG.\n\nTraining computer vision AI models requires massive, high-quality, diverse and unbiased datasets. These can be challenging and costly to obtain, especially with increasing demands both of and for AI.\n\nThe Rendered.ai platform-as-a-service helps to solve this issue by generating physically accurate synthetic data \u2014 data that\u2019s created from 3D simulations \u2014 to train computer vision models.\n\n\u201cReal-world data often can\u2019t capture all of the possible scenarios and edge cases necessary to generalize an AI model, which is where SDG becomes key for AI and machine learning engineers,\u201d said Nathan Kundtz, founder and CEO of Rendered.ai, which is based in Bellevue, Wash., a Seattle suburb.\n\nA member of the NVIDIA Inception program for cutting-edge startups, Rendered.ai has now integrated into its platform NVIDIA Omniverse Replicator , a core extension of the Omniverse platform for developing and operating industrial metaverse applications.\n\nOmniverse Replicator enables developers to generate labeled synthetic data for many such applications, including visual inspection, robotics and autonomous driving. It\u2019s built on open standards for 3D workflows, including Universal Scene Description (\u201cOpenUSD\u201d), Material Definition Language (MDL) and PhysX .\n\nSynthetic images generated with Rendered.ai have been used to model landscapes and vegetation for virtual worlds, detect objects in satellite imagery, and even test the viability of human oocytes, or egg cells.\n\nWith Rendered.ai tapping into the RTX -accelerated functionalities of Omniverse Replicator \u2014 such as ray tracing, domain randomization and multi-sensor simulation \u2014 computer vision engineers, data scientists and other users can quickly and easily generate synthetic data through a simple web interface in the cloud.\n\n\u201cThe data that we have to train AI is really the dominant factor on the AI\u2019s performance,\u201d Kundtz said. \u201cIntegrating Omniverse Replicator into Rendered.ai will enable new levels of ease and efficiency for users tapping synthetic data to train bigger, better AI models for applications across industries.\u201d\n\nRendered.ai will demonstrate its platform integration with Omniverse Replicator at the Conference on Computer Vision and Pattern Recognition (CVPR), running June 18-22 in Vancouver, Canada.\n\nRendered.ai, now available through AWS Marketplace, brings to the cloud a collaborative web interface for developers and teams to design SDG applications that can be easily configured by computer vision engineers and data scientists.\""
  },
  {
    "question": "What is the name of the architecture powering GeForce NOW Ultimate's upgraded RTX 4080 SuperPODs?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDEvMTIvZ2Vmb3JjZS1ub3ctdGh1cnNkYXktamFuLTEyLw==.pdf",
    "ground_truth_answer": "The NVIDIA Ada Lovelace architecture.",
    "ground_truth_context": "\"\nGeForce NOW Ultimate is cloud gaming that is \u201cbeyond fast.\u201d Powered by the NVIDIA Ada Lovelace architecture in upgraded GeForce NOW RTX 4080 SuperPODs, Ultimate members can stream at up to 240 frames per second for the lowest latency ever from the cloud, or up to 4K 120 fps.\n\nUltimate members can also take advantage of new ultrawide resolution support for their favorite PC games, and experience full ray tracing and DLSS 3 in supported titles for beautiful, cinematic-quality graphics.\n\nUltimate members can play today on GeForce NOW RTX 3080 rigs for the highest performance and lowest latency available in cloud gaming. And when GeForce RTX 4080-powered SuperPODs begin rolling out in North America and Europe later this month, Ultimate members will be the first to stream at RTX 4080-class power.\n\nSign up today \u2014 quantities are limited.\n\nGet the gaming going this weekend with seven more titles supported on GeForce NOW:\n\nTom Clancy\u2019s The Division 2 (New release on Steam , Jan. 12)\n\nDakar Desert Rally ( Epic Games )\n\nDestroy All Humans! ( Steam and Epic Games )\n\nDestroy All Humans! 2 \u2013 Reprobed ( Steam and Epic Games )\n\nMX vs ATV Legends ( Steam )\n\nThe Valiant ( Steam and Epic Games )\n\nWay of the Hunter ( Steam and Epic Games )\n\nWhile you\u2019re getting ready for an out-of-this-world weekend full of gaming, we\u2019ve got a question for you. Let us know your answer on Twitter or in the comments below. You look out your window and see an alien invasion happening. n What do you grab first? n \u2014 nn NVIDIA GeForce NOW (@NVIDIAGFN) January 11, 2023\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/01/12/geforce-now-thursday-jan-12/\""
  },
  {
    "question": "How can utilities use speech AI to drive new efficiencies and meet ever-rising customer expectations?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDkvMDcvc3BlZWNoLWFpLWZvci1pbmR1c3RyaWVzLw==.pdf",
    "ground_truth_answer": "Utilities can use speech AI for voice-based customer service, streamlining meter reading, supporting field technicians with voice notes and voice commands, and analyzing customer preferences with NLP. Minerva CQ, an AI assistant designed specifically for retail energy use cases, can transcribe conversations into text in real-time, analyze customer sentiment, intent, and propensity, and provide dialogue suggestions, behavioral cues, personalized offers, and sentiment analysis to customer service agents, enabling them to guide customers to the most ideal energy plan.",
    "ground_truth_context": "\"\nThis technology can ease the burden of manual note-taking and has the potential to accelerate insurance and billing processes while also creating consultation recaps for caregivers. Relieved of administrative tasks, physicians can focus on patient care to deliver superior experiences.\n\nArtisight, an AI platform for healthcare , uses speech recognition to power zero-touch check-ins and speech synthesis to notify patients in the waiting room when the doctor is available. Over 1,200 patients per day use Artisight kiosks, which help streamline registration processes, improve patient experiences, eliminate data entry errors with automation and boost staff productivity.\n\nAs healthcare moves toward a smart hospital model, expect to see speech AI play a bigger role in supporting medical professionals and powering low-touch experiences for patients. This may include risk factor prediction and diagnosis through clinical note analysis, translation services for multilingual care centers, medical dictation and transcription and automation of other administrative tasks.\n\nFaced with increasing demand for clean energy, high operating costs and a workforce retiring in greater numbers, energy and utility companies are looking for ways to do more with less.\n\nTo drive new efficiencies, prepare for the future of energy and meet ever-rising customer expectations, utilities can use speech AI. Voice-based customer service can enable customers to report outages, inquire about billing and receive support on other issues without agent intervention. Speech AI can streamline meter reading, support field technicians with voice notes and voice commands to access work orders and enable utilities to analyze customer preferences with NLP.\n\nMinerva CQ, an AI assistant designed specifically for retail energy use cases, supports customer service agents by transcribing conversations into text in real time. Text is fed into Minerva CQ\u2019s AI models, which analyze customer sentiment, intent, propensity and more.\n\nBy dynamically listening, the AI assistant populates an agent\u2019s screen with dialogue suggestions, behavioral cues, personalized offers and sentiment analysis. A knowledge-surfacing feature pulls up a customer\u2019s energy usage history and suggests decarbonization options \u2014 arming agents with the information needed to help customers make informed decisions about their energy consumption.\n\nWith the AI assistant providing consistent, simple explanations on energy sources, tariff plans, billing changes and optimal spending, customer service agents can effortlessly guide customers to the most ideal energy plan. After deploying Minerva CQ, one utility provider reported a 44% reduction in call handling time, a 12.5% increase in first-contact resolution and average savings of $2.67 per call.\""
  },
  {
    "question": "How does CCC's use of NVIDIA Base Command Platform impact their productivity?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDMvMjEvY2NjLWFpLWluc3VyYW5jZS1jbGFpbXMv.pdf",
    "ground_truth_answer": "CCC's use of NVIDIA Base Command Platform integrated with their development pipeline for training job orchestration and data management results in improved productivity, allowing data scientists to run experiments 2x faster, leading to more learnings and innovation.",
    "ground_truth_context": "\"\nWith 25-30% of its data scientists and engineering teams\u2019 time dedicated to experimentation, coupled with massive datasets that are growing each day, CCC needed to enable a more scalable, multi-platform, hybrid multi-cloud for its training environment.\n\nUsing its AI pipeline, CCC launched CCC Estimate \u2013 STP, which can deliver a detailed line-level estimate of the collision repair cost based on insurer rules in seconds using AI and just a few pictures of vehicle damage taken from a smartphone. Traditional methods can take several days.\n\nThis saves time for adjusters, freeing them up for more complex work. This digitalized estimation process helps elevate the customer experience as well as lower processing costs and is currently being used by leading insurance companies across the U.S.\n\nBut the results are broader. Using the NVIDIA Base Command Platform integrated with their development pipeline for training job orchestration and data management, the CCC team realizes improved productivity. Data scientists can run experiments 2x faster, which can mean more learnings for more innovation and solution development.\n\n\u201cWe run some experiments on premises on NVIDIA DGX systems, but we may have spikes where we want to add, for example, 10 million more data points and do another run,\u201d Hantehzadeh said. \u201cIf we need additional capacity, we can switch to DGX Cloud. Base Command Platform makes this process seamless.\u201d\n\nCCC plans to continue taking its investment to the leading edge of AI development, injecting AI and STP into different channels and products across the property and casualty insurance economy.\n\nLearn more about NVIDIA DGX Cloud and NVIDIA Base Command Platform .\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/03/21/ccc-ai-insurance-claims/\""
  },
  {
    "question": "What are the top four speech AI applications for contact centers?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDEvMTEvdG9wLXNwZWVjaC1haS1hcHBsaWNhdGlvbnMtY29udGFjdC1jZW50ZXJzLw==.pdf",
    "ground_truth_answer": "The top four speech AI applications for contact centers are: automating routine tasks and handling simple queries and requests, providing 24/7 convenience and multi-language support, quick and efficient human agent support, and unpredictable spike support.",
    "ground_truth_context": "\"\nTop 4 Speech AI Applications Transforming Contact Centers\n\nAuthor: Gordana Neskovic\n\nContact centers play a vital role in connecting businesses with their customers for service, sales and support \u2014 and to drive customer satisfaction.\n\nHowever, long wait times on the phone, communication difficulties and a lack of helpful information can lead to a stressful and frustrating experience for both customers and agents.\n\nSpeech AI applications help reduce these issues. Speech AI includes automatic speech recognition (ASR), which is the conversion of human voice to text, and text-to-speech (TTS), which is the generation of human-like voice from text.\n\nSpeech AI technology can also comprehend and generate different accents, languages and dialects, making it a powerful tool for businesses that operate in a global context.\n\nSpeech AI applications that advance automation are particularly well-suited for use in contact centers, as these can handle customers\u2019 transactional issues and simple requests, as well as predict and provide actionable insights tailored to individuals.\n\nThe top four applications of speech AI for contact centers are:\n\nContact centers face challenges in three main areas. Primary among them is customer satisfaction. Many customers expect 24/7 service, with short \u2014 if any \u2014 wait times, along with fast issue resolution. They want a personalized experience, preferably in their native language.\n\nAgent productivity is a second challenge, where a breadth and depth of information is required to adequately train contact-center agents and keep them updated on new offerings.\n\nThe third area is operations. Companies can struggle to provide contact-center agents with quick, easy policy changes and operational updates, which leads to high agent churn and increased customer service costs.\n\nConsidering these issues, speech AI applications provide the following benefits to contact centers:\n\nReduced customer wait times by automating routine tasks and handling simple queries and requests.\n\n24/7 convenience with availability to handle customer requests anytime, anywhere.\n\nMulti-language support to serve customers around the globe in their preferred language.\n\nQuick, efficient human agent support by providing the correct information to agents and customers at the appropriate time, as well as improved skills and knowledge for human agents using insights from call transcripts.\n\nUnpredictable spike support because speech AI applications can easily scale to meet demand.\n\nBetter products and services based on crowdsourced learning and call transcription insights and analyses.\n\nFrom financial services to telecom, speech AI applications are being used across many industries.\n\nThese applications integrate speech recognition, semantic comprehension and speech synthesis for realistic human-machine interaction when answering customer questions about insurance, banking, wireless calling plans and more.\""
  },
  {
    "question": "What is the benefit of using NVIDIA Metropolis for Factories for Pegatron?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDUvMjgvZWxlY3Ryb25pY3MtZ2lhbnRzLWluZHVzdHJpYWwtYXV0b21hdGlvbi1udmlkaWEtbWV0cm9wb2xpcy1mb3ItZmFjdG9yaWVzLw==.pdf",
    "ground_truth_answer": "Pegatron is able to achieve 99.8% accuracy on its AOI systems with NVIDIA Metropolis for Factories, starting with small datasets, and can quickly update its defect detection models.",
    "ground_truth_context": "\"\nElectronics Giants Tap Into Industrial Automation With NVIDIA Metropolis for Factories\n\nLeading Taiwanese manufacturers \u2014 including Foxconn Industrial Internet, Pegatron, Quanta and Wistron \u2014 are adopting Metropolis for Factories to handle automated optical inspections.\n\nAuthor: Adam Scraba\n\nThe $46 trillion global electronics manufacturing industry spans more than 10 million factories worldwide, where much is at stake in producing defect-free products. To drive product excellence, leading electronics manufacturers are adopting NVIDIA Metropolis for Factories.\n\nMore than 50 manufacturing giants and industrial automation providers \u2014 including Foxconn Industrial Internet, Pegatron, Quanta, Siemens and Wistron \u2014 are implementing Metropolis for Factories, NVIDIA founder and CEO Jensen Huang announced during his keynote address at the COMPUTEX technology conference in Taipei.\n\nNVIDIA Metropolis for Factories is a collection of factory automation workflows that enables industrial technology companies and manufacturers to develop, deploy and manage customized quality-control systems that offer a competitive advantage.\n\nManufacturers globally spend more than $6 trillion a year in pursuit of quality control, and they apply defect detection on nearly every product line. But manual inspections can\u2019t keep up with the demands.\n\nMany manufacturers have automated optical inspection (AOI) systems that can help, but often these have high false detection rates, requiring labor-intensive and costly secondary manual inspections in an already challenging labor market, reducing their value.\n\nNVIDIA Metropolis for Factories now offers a state-of-the-art AI platform and workflows for the development of incredibly accurate inspection applications such as AOI.\n\nLeading manufacturer Pegatron , based in Taipei\u2019s Beitou district, is using NVIDIA Metropolis for Factories on its production lines.\n\nPegatron manufactures everything from motherboards to smartphones, laptops and game consoles. With a dozen manufacturing facilities handling more than 300 products and more than 5,000 parts per day, Pegatron has a lot of quality control to manage across its product portfolio. Further, frequent product updates require ongoing revisions to its AOI systems.\n\nPegatron is using the entire Metropolis for Factories workflow to support its printed circuit board (PCB) factories with simulation, robotics and automated production inspection. Metropolis for Factories enables the electronics manufacturing giant to quickly update its defect detection models and achieve 99.8% accuracy on its AOI systems, starting with small datasets.\n\nPegatron uses NVIDIA Isaac Sim , a robotic simulator, to program robotic arms in simulation and to model the performance of its fleets of mobile robots.\n\nTapping into NVIDIA Omniverse Replicator provides synthetic data generation to simulate defects, helping build massive training datasets with domain randomization and other techniques.\""
  },
  {
    "question": "What is the name of the publisher that has added seven new titles to the GeForce NOW library?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDEvMTIvZ2Vmb3JjZS1ub3ctdGh1cnNkYXktamFuLTEyLw==.pdf",
    "ground_truth_answer": "The publisher that has added seven new titles to the GeForce NOW library is THQ Nordic.",
    "ground_truth_context": "\"\nGFN Thursday Adds New Titles From THQ Nordic to GeForce NOW\n\n\u2018Destroy All Humans,\u2019 \u2018The Valiant\u2019 lead seven new additions this week.\n\nAuthor: GeForce NOW Community\n\nGFN Thursday kicks each weekend off with new games and updates straight from the cloud. This week adds more games from publisher THQ Nordic to the GeForce NOW library , as part seven total additions.\n\nMembers can gear up to play these new titles the ultimate way with the upcoming release of the new Ultimate membership , delivering RTX 4080-class performance and elevated cloud gaming perks.\n\nJust announced at CES 2023, HP is adding support for NVIDIA GeForce NOW through its OMEN Gaming Hub. Members will have access to the GeForce NOW library of over 1,500 titles built right into their latest HP laptops, making it even easier to stream at GeForce quality.\n\nAdventure to new and strange worlds with support for five THQ Nordic titles coming to the GeForce NOW library. Members can stream the Steam and Epic Games Store versions from their favorite digital stores across all GeForce NOW-compatible devices.\n\nFollow the story of a former crusader knight called back into action to stop the unification of a powerful ancient artifact that could bring untold evil to the world in The Valiant . Rally warriors with different skills to the cause and build custom hero-squads to defeat your enemies. Stream from PC and Mac apps even in 4K resolution with the GeForce NOW Ultimate membership .\n\nPlay as evil alien Crypto-137 harvesting DNA from Earth\u2019s citizens in the brazen action-adventure title Destroy All Humans! . Use an assortment of alien weaponry and psychic skills to bring down the government and reduce cities of the 1950s to rubble with a flying saucer.\n\nCrypto the alien invader returns, groovier than ever, in Destroy All Humans! 2: Reprobed , the swinging sequel set in the \u201860s. Stream your intergalactic adventures on the big screen with NVIDIA SHIELD or Samsung Smart TVs in beautiful 4K.\n\nBecome the new owner of a hunting lodge, explore vast open-world environments, and hunt with a premium selection of firearms and equipment in Way of the Hunter . Enjoy the hunt on your own or with a friend in multiplayer co-op, and experience the great outdoors on the go playing from mobile devices .\n\nExperience high-intensity outdoor racing and become a world-famous, professional off-road rider in MX vs ATV Legends . Compete against others in the new career mode, where choices lead to different paths on devices designed for enhanced streaming experiences like the Logitech G CLOUD or cloud gaming Chromebooks .\n\nReady for the ultimate cloud gaming performance? Upgrade to a GeForce NOW Ultimate membership and get ready for RTX 4080-class performance the moment it\u2019s available.\""
  },
  {
    "question": "What is the name of the latest version of NVIDIA's AI-powered Deep Learning Super Sampling technology?",
    "document": "TmV1cmFsIEdyYXBoaWNzIERMU1MgMyAzLzE2LzIzLnBkZg==.pdf",
    "ground_truth_answer": "The latest version of NVIDIA's AI-powered Deep Learning Super Sampling technology is DLSS 3.",
    "ground_truth_context": "\"\nNVIDIA Accelerates Neural Graphics PC Gaming Revolution at GDC With New DLSS 3 PC Games and Tools\n\nAI-Powered NVIDIA DLSS 3 Comes to New AAA Games Including Diablo IV; DLSS Frame Generation Publicly Available for Developers at GDC\n\nAhead of next week\u2019s Game Developers Conference (GDC), NVIDIA announced an expanded game roster and new developer plug-ins for NVIDIA DLSS 3.\n\nThe latest version of NVIDIA\u2019s AI-powered Deep Learning Super Sampling (DLSS) technology is now supported in an assortment of blockbuster games and franchises, and being integrated into Unreal Engine, one of the world\u2019s most popular game engines. The company is also publicly releasing the DLSS Frame Generation plug-in to further ease developer adoption of the technology.\n\n\u201cNeural graphics has revolutionized gaming since its introduction with NVIDIA DLSS, and we\u2019re now taking it to new heights,\u201d said Matt Wuebbling, vice president of global GeForce marketing at NVIDIA. \u201cPC gaming super-franchises such as Diablo and Forza Horizon and Bethesda\u2019s new Redfall are raising the bar for image quality with stunning graphics while using DLSS to keep gameplay smooth as silk.\u201d\n\nSince its launch in 2018, NVIDIA DLSS has driven a neural graphics revolution in PC gaming. Neural graphics intertwines AI and graphics to create an accelerated rendering pipeline that continuously learns and improves. Instead of natively rendering every pixel in a frame, DLSS allows the game to render 1/8th of the pixels then uses AI and GeForce RTX\u2122 Tensor Cores to reconstruct the rest of the pixels, dramatically multiplying frame rates, while delivering crisp, high-quality images that rival native resolution.\n\nDiablo IV, Forza Horizon 5, Redfall \u2014 DLSS 3 is in the Biggest Games and Biggest Franchises To date, over 270 games and applications use NVIDIA DLSS as an AI-powered performance accelerator. DLSS 3, the latest version of the technology, is available in 28 released games and has been adopted 7x faster than DLSS 2 in the first six months of their respective launches.\n\nAmong the highly anticipated games being added to the DLSS roster is Forza Horizon 5, named the best open-world racing game of all time by several media outlets and currently holding the highest rating of any racing game tracked by OpenCritic. Forza Horizon 5, which already supports ray tracing, will update to DLSS 3 on March 28.\n\nRedfall, Bethesda\u2019s highly anticipated, open-world, co-op first-person shooter from Arkane Austin, the award-winning team behind Prey and Dishonored, is launching on May 2 with DLSS 3.\n\nIn addition, Diablo IV, the latest installment of the genre-defining Diablo franchise \u2014 multiple games of which are considered among the best of all time \u2014 will be launching on June 6 with DLSS 3.\""
  },
  {
    "question": "What is the benefit of connecting live data from the physical world to digital twins?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTIvMTkvZWRnZS1haS10cmVuZHMtMjAyMy8=.pdf",
    "ground_truth_answer": "Connecting live data from the physical world to digital twins allows organizations to gain real-time insight into their environment, enabling them to make faster and more informed decisions.",
    "ground_truth_context": "\"\nWith billions of devices and sensors around the world that will all be connected to the internet, IT organizations have to both protect edge devices from direct attack and consider network and cloud security. In 2023, expect to see AI applied to cybersecurity . Log data generated from IoT networks can now be fed through intelligent security models that can flag suspicious behavior and notify security teams to take action.\n\nThe term digital twin refers to perfectly synchronized, physically accurate virtual representations of real-world assets, processes or environments. Last year, NVIDIA partnered with Siemens to enable industrial metaverse use cases, helping customers accelerate their adoption of industrial automation technologies. Leading companies spanning manufacturing, retail, consumer packaged goods and telco, such as BMW , Lowe\u2019s , PepsiCo and Heavy.AI , have also begun building operational digital twins allowing them to simulate and optimize their production environments.\n\nWhat connects digital twins to the physical world and edge computing is the explosion of IoT sensors and data that is driving both these trends. In 2023, we\u2019ll see organizations increasingly connect live data from their physical environment into their virtual simulations. They\u2019ll move away from historical data-based simulations toward a live, digital environment \u2014 a true digital twin.\n\nBy connecting live data from the physical world to their digital twins, organizations can gain real-time insight into their environment, allowing them to make faster and more informed decisions. While still early, expect to see massive growth in this space next year for ecosystem providers and in customer adoption.\n\nWhile the 2023 economic environment remains uncertain, edge AI will certainly be an area of investment for organizations looking to drive automation and efficiency. Many of the trends we saw take off last year continue to accelerate with the new focus on initiatives that help drive sales, reduce costs, grow customer satisfaction and enhance operational efficiency.\n\nVisit NVIDIA\u2019s Edge Computing Solutions page to learn more about edge AI and how we\u2019re helping organizations implement it in their environments today.\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/12/19/edge-ai-trends-2023/\""
  },
  {
    "question": "What is ArtSquad?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTEvMDQvcmFmaS1uaXphbS1vbW5pdmVyc2UtY3JlYXRvci8=.pdf",
    "ground_truth_answer": "ArtSquad is an upcoming computer-graphics-animated series created by Rafi Nizam, featuring fun-loving, vibrant 3D characters who form a band and solve problems through the power of art.",
    "ground_truth_context": "\"\nMeet the Omnivore: Indie Showrunner Transforms Napkin Doodles Into Animated Shorts With NVIDIA Omniverse\n\nU.K.-based Rafi Nizam creates animated show \u2018ArtSquad\u2019 using Omniverse Create XR and content-creation apps from Adobe, Autodesk, Epic Games and more.\n\nAuthor: Angie Lee\n\nEditor\u2019s note: This post is a part of our Meet the Omnivore series, which features individual creators and developers who use NVIDIA Omniverse to accelerate their 3D workflows and create virtual worlds.\n\n3D artist Rafi Nizam has worn many hats since starting his career as a web designer more than two decades ago, back when \u201cdesigning for the web was still wild,\u201d as he put it.\n\nHe\u2019s now becoming a leader in the next wave of creation \u2014 using extended reality and virtual production \u2014 with the help of NVIDIA Omniverse , a platform for building and connecting custom 3D pipelines.\n\nThe London-based showrunner, creative consultant and entertainment executive previously worked at advertising agencies and led creative teams at Sony Pictures, BBC and NBCUniversal.\n\nIn addition to being an award-winning independent animator, director, character designer and storyteller who serves as chief creative officer at Masterpiece Studio, he\u2019s head of story at game developer Opis Group, and showrunner at Lunar-X, a next-gen entertainment company.\n\nPlus, in recent years, he\u2019s taken on what he considers his most important role of all \u2014 being a father. And his art is now often inspired by family.\n\n\u201cBeing present in the moment with my children and observing the world without preconceptions often sparks ideas for me,\u201d Nizam said.\n\nHis animated shorts have so far focused on themes of self care and finding stillness amidst chaos. He\u2019s at work on a new computer-graphics-animated series, ArtSquad , in which fun-loving, vibrant 3D characters form a band, playing instruments made of classroom objects and solving problems through the power of art.\n\n\u201cThe myriad of 3D apps in my animation pipeline can sync and come together in Omniverse using the Universal Scene Description framework,\u201d he said. \u201cThis interoperability allows me to be 10x more productive when visualizing my show concepts \u2014 and I\u2019ve cut my outsourcing costs by 50%, as Omniverse enables me to render, lookdev, lay out scenes and manipulate cameras by myself.\u201d\n\nNizam said he often starts his projects with \u201cgood ol\u2019 pencil and paper on a Post-it note or napkin, whenever inspiration strikes.\u201d\n\nHe then takes his ideas to a drawing desk, where he creates a simple sketch before honing in on pre-production using digital content-creation apps like Adobe Illustrator, Adobe Photoshop and Procreate.\n\nNizam next creates 3D production assets from his 2D sketches, manipulating them in virtual reality using Adobe Substance 3D Modeler software.\n\n\u201cThings start to move pretty rapidly from here,\u201d he said, \u201cbecause VR is such an intuitive way to make 3D assets. Plus, rigging and texturing in the Masterpiece Studio creative suite and Adobe Substance\""
  },
  {
    "question": "How does Mediobanca reduce its total cost of ownership while accelerating workloads?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTIvMTMvYWNjZWxlcmF0ZWQtY29tcHV0aW5nLW1pbGFuLWJhbmsv.pdf",
    "ground_truth_answer": "Mediobanca reduces its total cost of ownership while accelerating workloads by using excellence in math and numeric methods of finance, which are closely related to those found in theoretical physics.",
    "ground_truth_context": "\"\nThat means Mediobanca can do more with less. It reduces its total cost of ownership while accelerating workloads that create competitive advantages such as Monte Carlo simulations used to create and price advanced investment products.\n\nUnder the hood, great financial performance is based on excellence in math, said Airoldi, who earned his Ph.D. in theoretical condensed matter physics.\n\n\u201cThe mathematical models and numeric methods of finance are closely related to those found in theoretical physics, so investment banking is a great job for a physicist,\u201d he said.\n\nWhen Airoldi needs a break from work, you might find him playing chess in the Piazza della Scala, across from the famed opera house, just around the corner from the bank\u2019s headquarters.\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/12/13/accelerated-computing-milan-bank/\""
  },
  {
    "question": "What is the name of the keynote speaker at GTC on Sept. 20, 2022?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDkvMDEvZ3RjLWRpZ2l0YWwtdHdpbnMv.pdf",
    "ground_truth_answer": "Jensen Huang.",
    "ground_truth_context": "\"\nRegister free for GTC and watch NVIDIA founder and CEO Jensen Huang\u2019s keynote on Tuesday, Sept. 20, at 8 a.m. PT to hear about the latest technology breakthroughs.\n\nFeature image courtesy of Amazon Robotics.\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/09/01/gtc-digital-twins/\""
  },
  {
    "question": "Who is the CEO of NVIDIA and what will they be discussing at GTC?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDgvMTgvZGlzY292ZXItZnJvbnRpZXJzLWFpLWF1dG9ub21vdXMtdmVoaWNsZXMtZ3RjLw==.pdf",
    "ground_truth_answer": "Jensen Huang is the CEO of NVIDIA and they will be discussing the latest in AI and NVIDIA Omniverse in the keynote address at GTC.",
    "ground_truth_context": "\"\nBoldly Go: Discover New Frontiers in AI-Powered Transportation at GTC See how NVIDIA DRIVE and its ecosystem are pushing the boundaries of autonomous driving at the technology conference for the era of AI.\n\nAuthor: Katie Burke\n\nAI and the metaverse are revolutionizing every aspect of the way we live, work and play \u2014 including how we move.\n\nLeaders in the automotive and technology industries will come together at NVIDIA GTC to discuss the newest breakthroughs driving intelligent vehicles, whether in the real world or in simulation.\n\nThe virtual conference, which runs from Sept. 19-22, will feature a slate of in-depth sessions on end-to-end software-defined vehicle development, as well as advances in robotics, healthcare, high performance computing and more. And it\u2019s all free to attend.\n\nHeadlining GTC is NVIDIA founder and CEO Jensen Huang, who will present the latest in AI and NVIDIA Omniverse in the keynote address on Tuesday, Sept. 20, at 8 a.m. PT.\n\nConference attendees will have plenty of networking opportunities, and they can learn from NVIDIA experts and industry luminaries about AV development, from the cloud to the car.\n\nHere\u2019s a brief look at what to expect during GTC:\n\nEvery stage of the automotive pipeline is being transformed by AI and metaverse technologies, from manufacturing and design, to autonomous driving, to the passenger experience.\n\nSpeakers from each of these areas will share how they\u2019re harnessing AI innovations to accelerate software-defined transportation.\n\nAutomotive sessions include:\n\nMichael Bell, senior vice president of Digital at Lucid Motors, walks through the development of the Lucid Dream Drive Pro advanced driver assistance system, and how the company continuously deploys new features for a cutting-edge driving experience.\n\nYuli Bai, head of AI Platform at NIO, outlines the AI infrastructure that the automaker is using to develop intelligent, software-defined vehicles running on the NVIDIA DRIVE Orin compute platform.\n\nApeksha Kumavat, chief engineer and co-founder at Gatik, explains how its autonomous commercial-delivery vehicles are helping the retail industry adapt to rapidly changing consumer demands.\n\nDennis Nobelius, chief operating officer at Polestar, describes how the performance electric vehicle maker is developing AI-powered features geared toward the human driver, while prioritizing long-term environmental sustainability.\n\nDon\u2019t miss additional sessions from BMW , Mercedes-Benz and Waabi covering manufacturing, AI research and more.\n\nLearn about the latest NVIDIA DRIVE technologies directly from the minds behind their creation.\n\nNVIDIA DRIVE Developer Day consists of a series of deep-dive sessions on building safe and robust autonomous vehicles. Led by the NVIDIA engineering team, the talks will highlight the newest DRIVE features and discuss how to apply them to AV development.\n\nTopics include:\n\nNVIDIA DRIVE product roadmap\n\nIntelligent in-vehicle infotainment\n\nData center development\""
  },
  {
    "question": "What is the name of the new technology preview coming to Cyberpunk 2077 that will allow for full ray tracing?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDMvMjMvZ2Vmb3JjZS1ub3ctdGh1cnNkYXktbWFyY2gtMjMv.pdf",
    "ground_truth_answer": "Ray Tracing: Overdrive Mode",
    "ground_truth_context": "\"\nContent developers have a slew of opportunities to bring their virtual worlds and interactive experiences to users in unique ways, powered by the cloud.\n\nMetaverse services company Improbable will use NVIDIA cloud gaming infrastructure for an interactive, live, invite-only experience that will accommodate up to 10,000 guests. Other recent developer events included the DAF Trucks virtual experience , where potential customers took the newest DAF truck for\n\na test drive in a simulated world, with PixelMob\u2019s Euro Truck Simulator 2 providing the virtual playground.\n\nFurthermore, CD PROJEKT RED will be delivering full ray tracing, aka path tracing , to Cyberpunk 2077. Such effects were previously only possible for film and TV. With the power of a GeForce RTX 4080 gaming rig in the cloud, Ultimate members will be able to stream the new technology preview for the Ray Tracing: Overdrive Mode coming to Cyberpunk 2077 across devices \u2014 even Macs \u2014 no matter the game\u2019s system requirements.\n\nGeForce NOW Ultimate members have been enjoying Marvel\u2019s Midnight Suns \u2019 ultra-smooth, cinematic game play thanks to DLSS 3 technology support on top of RTX-powered ray tracing, which together enable graphics breakthroughs.\n\nNow, members can fight among the legends with Captain Marvel\u2019s Medieval Marvel suit in a free reward, which will become available at the end of the month \u2014 first to Premium members who are opted into GeForce NOW rewards. This reward is only available until May 6, so upgrade to an Ultimate or Priority membership today and opt into rewards to get first access.\n\nNext, on to the five new games hitting GeForce NOW week for a happy weekend:\n\nTchia (New release on Epic Games Store )\n\nChess Ultra (New release on Epic Games Store , March 23)\n\nAmberial Dreams ( Steam )\n\nSymphony of War: The Nephilim Saga ( Steam )\n\nNo One Survived ( Steam )\n\nAnd with that, we\u2019ve got a question to end this GFN Thursday:\n\nYouve got free rent for a year to live in a video game city of your choice, which one are you choosing? n\n\n\u2014 nn NVIDIA GeForce NOW (@NVIDIAGFN) March 22, 2023\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/03/23/geforce-now-thursday-march-23/\""
  },
  {
    "question": "What is the name of the largest mammal?",
    "document": "RmluYW5jaWFsIFJlc3VsdHMgUTJGWTI0IDgvMjMvMjMucGRm.pdf",
    "ground_truth_answer": "The blue whale.",
    "ground_truth_context": "\"\n\u00a9 2023 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, BlueField, GeForce, GeForce RTX, NVIDIA DGX, NVIDIA DRIVE Orin, NVIDIA Grace Hopper, NVIDIA Hopper, NVIDIA MGX, NVIDIA Omniverse, NVIDIA OVX, NVIDIA RTX, and NVIDIA Spectrum-X are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and/or other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability, and specifications are subject to change without notice.\n\nSimona Jankowski Investor Relations sjankowski@nvidia.com Robert Sherbin Corporate Communications rsherbin@nvidia.com\n\n71.5%\n\n1.0%\n\n72.5%\n\n2,950\n\n(950)\n\n2,000\""
  },
  {
    "question": "How are companies meeting consumer expectations with speech AI?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDkvMDcvc3BlZWNoLWFpLWZvci1pbmR1c3RyaWVzLw==.pdf",
    "ground_truth_answer": "Speech AI can understand and converse in natural language, creating opportunities for seamless, multilingual customer interactions while supplementing employee capabilities. It can power self-serve banking, enable food kiosk avatars, transcribe clinical notes, and streamline bill payments, helping businesses across industries deliver personalized customer experiences.",
    "ground_truth_context": "\"\nHow Industries Are Meeting Consumer Expectations With Speech AI Artificial intelligence is transforming customer experiences and helping companies provide on-demand service, fast delivery and personalized interactions.\n\nAuthor: Cliff Edwards\n\nThanks to rapid technological advances, consumers have become accustomed to an unprecedented level of convenience and efficiency.\n\nSmartphones make it easier than ever to search for a product and have it delivered right to the front door. Video chat technology lets friends and family on different continents connect with ease. With voice command tools, AI assistants can play songs, initiate phone calls or recommend the best Italian food in a 10-mile radius. AI algorithms can even predict which show users may want to watch next or suggest an article they may want to read before making a purchase.\n\nIt\u2019s no surprise, then, that customers expect fast and personalized interactions with companies. According to a Salesforce research report , 83% of consumers expect immediate engagement when they contact a company, while 73% expect companies to understand their unique needs and expectations. Nearly 60% of all customers want to avoid customer service altogether, preferring to resolve issues with self-service features.\n\nMeeting such high consumer expectations places a massive burden on companies in every industry, including on their staff and technological needs \u2014 but speech AI can help.\n\nSpeech AI can understand and converse in natural language, creating opportunities for seamless, multilingual customer interactions while supplementing employee capabilities. It can power self-serve banking in the financial services industry , enable food kiosk avatars in restaurants , transcribe clinical notes in healthcare facilities or streamline bill payments for utility companies \u2014 helping businesses across industries deliver personalized customer experiences.\n\nMost people now use both digital and traditional channels to access banking services, creating a demand for omnichannel, personalized customer support. However, higher demand for support coupled with a high agent churn rate has left many financial institutions struggling to keep up with the service and support needs of their customers.\n\nCommon consumer frustrations include difficulty with complex digital processes, a lack of helpful and readily available information, insufficient self-service options, long call wait times and communication difficulties with support agents.\n\nAccording to a recent NVIDIA survey , the top AI use cases for financial service institutions are natural language processing (NLP) and large language models (LLMs) . These models automate customer service interactions and process large bodies of unstructured financial data to provide AI-driven insights that support all lines of business across financial institutions \u2014 from risk management and fraud detection to algorithmic trading and customer service.\""
  },
  {
    "question": "What is the name of the new Saints Row game?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDgvMDQvZ2Vmb3JjZS1ub3ctdGh1cnNkYXktYXVndXN0LTQv.pdf",
    "ground_truth_answer": "The new Saints Row game is called Saints Row.",
    "ground_truth_context": "\"\nRush Into August This GFN Thursday With 38 New Games on GeForce NOW A new month of gaming brings new release titles like \u2018Saints Row,\u2019 \u2018Rumbleverse\u2019 and more, with 13 games streaming this week.\n\nAuthor: GeForce NOW Community\n\nIt\u2019s the first GFN Thursday of the month and you know the drill \u2014 GeForce NOW is bringing a big batch of games to the cloud.\n\nGet ready for 38 exciting titles like Saints Row and Rumbleverse arriving on the GeForce NOW library in August. Members can kick off the month streaming 13 new games today, including Retreat to Enen with RTX ON.\n\nThis month is packed full of new games streaming across GeForce NOW-supported devices. Gamers have 38 new titles to look forward to, including exciting new releases like Saints Row and Rumbleverse that can be played on Macs only via the power of the GeForce cloud.\n\nMembers will be able to visit the Weird Wild West of Santo Ileso, a vibrant city rife with crime in Deep Silver\u2019s explosive franchise reboot of Saints Row . Embark on criminal ventures as the future Boss, form the Saints with allies Neenah, Kevin and Eli, take down competing gangs, and build your criminal empire to become truly Self Made.\n\nGamers will also be able to throw down in Rumbleverse , a new, free-to-play, 40-person Brawler Royale where anyone can be a champion. Customize your fighter by mixing and matching unique items and launch your way into the battlefield, streaming at full PC quality to mobile devices .\n\nRTX 3080 members will also be able to play these and the other 1,300+ titles in the GeForce NOW library streaming in 4K resolution at 60 frames per second, or 1440p at 120 FPS on PC and Mac native apps .\n\nCatch the full list of games coming to the cloud later this August:\n\nTyrant\u2019s Blessing (New release on Steam , Aug. 8)\n\nFarthest Frontier (New release on Steam , Aug. 9)\n\nArcade Paradise (New release on Steam and Epic Games Store , Aug. 11)\n\nRumbleverse (New release on Epic Games Store , Aug. 11)\n\nCult of the Lamb (New release on Steam , Aug. 11)\n\nThymesia (New release on Steam , Aug. 18)\n\nUltimate Fishing Simulator 2 (New release on Steam , Aug. 22)\n\nFallen Legion Revenants (New release on Steam and Epic Games Store , Aug. 23)\n\nSaints Row (New release on Epic Games Store , Aug. 23)\n\nThe Bridge Curse: Road to Salvation (New release on Steam , Aug. 25)\n\nF1 Manager 2022 (New release on Steam and Epic Games Store , Aug. 30)\n\nScathe (New release on Steam , Aug. 31)\n\nMondealy (New release on Steam , Aug. 31)\n\nCentury: Age of Ashes ( Steam and Epic Games Store )\n\nClanfolk ( Steam )\n\nCoromon ( Steam and Epic Games Store )\n\nDark Deity Name ( Steam and Epic Games Store )\n\nHotline Miami 2: Wrong Number ( Steam )\n\nHYPERCHARGE: Unboxed ( Steam and Epic Games Store )\n\nInfinite Lagrange ( Steam )\n\nLast Call BBS ( Steam )\n\nLumencraft ( Steam )\n\nPhoenix Point ( Epic Games Store )\n\nPlague Inc: Evolved ( Steam )\n\nRebel Inc: Escalation ( Steam )\n\nGreat gaming in August starts with 13 new games now ready to stream.\""
  },
  {
    "question": "What is the benefit of using Clara Holoscan SDK?",
    "document": "Q2xhcmEgSG9sb3NjYW4gTUdYIDMvMjIvMjIucGRm.pdf",
    "ground_truth_answer": "Clara Holoscan SDK allows developers to build the next generation of software-defined instruments, bringing together pretrained models and a framework for scalable microservices, and enabling applications to be managed and deployed both on device and on the edge data center, ushering in the software-as-a-service business model for the industry.",
    "ground_truth_context": "\"\nMedical device makers can directly embed Clara Holoscan MGX or connect to the existing install base of medical devices, which allows developers to accelerate AI deployment and regulatory clearance.\n\nThe Clara Holoscan SDK is specifically designed for high-performance streaming applications to build the next generation of software-defined instruments. It brings together pretrained models, as well as a framework for scalable microservices, to allow applications to be managed and deployed both on device and on the edge data center, ushering in the software-as-a- service business model for the industry.\n\nClara Holoscan extends from medical devices to NVIDIA edge servers to NVIDIA DGX\u2122 systems in the cloud or the data center.\n\nClara Holoscan developer kits are available today. Join the interest list for Clara Holoscan MGX to get notified about availability.\n\nTo learn more about Clara Holoscan MGX, watch the GTC 2022 keynote from NVIDIA CEO Jensen Huang. Register for GTC for free to attend sessions with NVIDIA and industry leaders.\n\nAbout NVIDIA NVIDIA\u2019s (NASDAQ: NVDA) invention of the GPU in 1999 sparked the growth of the PC gaming market and has redefined modern computer graphics, high performance computing and artificial intelligence. The company\u2019s pioneering work in accelerated computing and AI is reshaping trillion-dollar industries, such as transportation, healthcare and manufacturing,\n\nand fueling the growth of many others. More information at https://nvidianews.nvidia.com/.\""
  },
  {
    "question": "What is the name of the AI-powered motion capture technology discussed in the 'AI-Powered, Real-Time, Markerless: The New Era of Motion Capture' session?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDIvMTQvaW4tdGhlLW52aWRpYS1zdHVkaW8tZmVicnVhcnktMTQv.pdf",
    "ground_truth_answer": "The AI-powered motion capture technology discussed in the 'AI-Powered, Real-Time, Markerless: The New Era of Motion Capture' session is called 'Omniverse'.",
    "ground_truth_context": "\"\nCatch these sessions live or watch on demand:\n\n3D Art Goes Multiplayer: Behind the Scenes of Adobe Substance\u2019s \u201cEnd of Summer\u201d Project With Omniverse [ S51239 ]\n\n3D and Beyond: How 3D Artists Can Build a Side Hustle in the Metaverse [ SE52117 ]\n\nNVIDIA Omniverse User Group [ SE52047 ]\n\nAccelerate the Virtual Production Pipeline to Produce an Award-Winning Sci-Fi Short Film [ S51496 ]\n\n3D by AI: How Generative AI Will Make Building Virtual Worlds Easier [ S52163 ]\n\nCustom World Building With AI Avatars: The Little Martians Sci-Fi Project [ S51360 ]\n\nAI-Powered, Real-Time, Markerless: The New Era of Motion Capture [ S51845 ]\n\nSearch the GTC session catalog or check out the Media and Entertainment and Omniverse topics for additional creator-focused talks.\n\nFollow NVIDIA Studio on Instagram , Twitter and Facebook . Access tutorials on the Studio YouTube channel and get updates directly in your inbox by subscribing to the Studio newsletter . Learn more\n\nabout Omniverse on Instagram , Medium , Twitter and YouTube for additional resources and inspiration. Check out the Omniverse forums , and join our Discord server and Twitch channel to chat with the community.\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/02/14/in-the-nvidia-studio-february-14/\""
  },
  {
    "question": "What was the name of the template that Luke added to his Adobe After Effects project?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDgvMTUvbWFybW9zZXQtdG9vbGJhZy1qaWZmeXZmeC1zdHVkaW8tbGFwdG9wcy8=.pdf",
    "ground_truth_answer": "The Doors to Realities template.",
    "ground_truth_context": "\"\nHis GeForce graphics card enabled RTX-accelerated OptiX ray tracing in the viewport for interactive, photorealistic rendering. When the final renders were ready, Luke added the Doors to Realities template into an Adobe After Effects project with the clip already masked and ready to go. There, he added glow effects, one of over 30+ GPU-accelerated key effects, with keyframes set up from previous videos.\n\n\u201cThe fact that I was able to work in rendered mode in real time on a device as small and portable as the Zenbook was mind blowing.\u201d \u2014 JiffyVFX\n\n\u201cAll I had to do was plop the render in, copy and paste the glow effects with their intensity keyframes and then hit render again,\u201d said Luke.\n\nFinally, Luke added music and background sounds like bird chirping, a river stream and the sound of leaves subtly blowing in the wind.\n\nThe Studio laptop not only enhances Luke\u2019s content creation experience but also boosts the efficiency of his workflow. \u201cHigh frame rates, DLSS 3 and ray tracing \u2014 what\u2019s not to love?\u201d said Luke.\n\nHe encourages other creators to push forward and continue experimenting.\n\n\u201cNever. Stop. Creating!\u201d said Luke. \u201cNever stop learning! The only way to improve is to keep pushing yourself and the limits of what you can do.\u201d\n\nCheck out JiffyVFX on TikTok .\n\nFollow NVIDIA Studio on Instagram , Twitter and Facebook . Access tutorials on the Studio YouTube channel and get updates directly in your inbox by subscribing to the Studio newsletter .\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/08/15/marmoset-toolbag-jiffyvfx-studio-laptops/\""
  },
  {
    "question": "What is the name of the developer who created a functional Iron Man helmet using the NVIDIA Jetson platform?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDIvMjMvbWlsbGlvbi1qZXRzb24tZGV2ZWxvcGVycy1ndGMv.pdf",
    "ground_truth_answer": "Kris Kersey",
    "ground_truth_context": "\"\nNVIDIA Celebrates 1 Million Jetson Developers Worldwide at GTC\n\nNVIDIA Jetson Edge AI Developer Days to share the latest on the embedded computing platform.\n\nAuthor: Jason Black\n\nA million developers across the globe are now using the NVIDIA Jetson platform for edge AI and robotics to build innovative technologies. Plus, more than 6,000 companies \u2014 a third of which are startups \u2014 have integrated the platform with their products.\n\nThese milestones and more will be celebrated during the NVIDIA Jetson Edge AI Developer Days at GTC , a global conference for the era of AI and the metaverse, taking place online March 20-23.\n\nRegister free to learn more about the Jetson platform and begin developing the next generation of edge AI and robotics.\n\nAtlanta-based Kris Kersey, the mind behind the popular YouTube channel Kersey Fabrications , is one developer using the NVIDIA Jetson platform for his one-in-a-million technological innovations.\n\nHe created a fully functional Iron Man helmet that could be straight out of the Marvel Comics films. It uses the NVIDIA Jetson Xavier NX 8GB developer kit as the core of the \u201cArc Reactor\u201d powering its heads-up display \u2014 a transparent display that presents information wherever the user\u2019s looking.\n\nIn just over two years, Kersey built from scratch the wearable helmet, complete with object detection and other on-screen sensors that would make Tony Stark proud.\n\n\u201cThe software design was more than half the work on the project, and for me, this is the most exciting, interesting part,\u201d Kersey said. \u201cThe software takes all of the discrete hardware components and makes them into a remarkable system.\u201d\n\nTo get started, Kersey turned to GitHub where he found \u201c Hello AI World ,\u201d a guide for deploying deep-learning inference networks and deep vision primitives with the NVIDIA TensorRT software development kit and NVIDIA Jetson. He then wrote a wrapper code to connect his own project.\n\nWatch Kersey document his Iron Man project from start to finish:\n\nThis 3D-printed helmet is just the beginning for Kersey, who\u2019s aiming to build a full Iron Man suit later this year. He plans to make the entire project\u2019s code open source, so anyone who dreams of becoming a superhero can try it for themselves.\n\nDevelopers like Kersey can register for the free Jetson Edge AI Developer Days at GTC, which feature NVIDIA experts who\u2019ll cover the latest Jetson hardware, software and partners. Sessions include:\n\nLevel Up Edge AI and Robotics With NVIDIA Jetson Orin Platform\n\nAccelerate Edge AI With NVIDIA Jetson Software\n\nGetting the Most Out of Your Jetson Orin Using NVIDIA Nsight Developer Tools\n\nBring Your Products to Market Faster With the NVIDIA Jetson Ecosystem\n\nDesign a Complex Architecture on NVIDIA Isaac ROS\""
  },
  {
    "question": "What is the potential of generative AI in the art industry?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDEvMTgvc2VxdW9pYS1jYXBpdGFsLWdlbmVyYXRpdmUtYWkv.pdf",
    "ground_truth_answer": "Generative AI has the potential to revolutionize the art industry by allowing for the creation of unique, personalized content on a scale that would be impossible for humans to achieve alone.",
    "ground_truth_context": "\"\nSequoia Capital\u2019s Pat Grady and Sonya Huang on Generative AI\n\nAuthor: Brian Caulfield\n\nFor insights into the future of generative AI , check out the latest episode of the NVIDIA AI Podcast . Host Noah Kravitz is joined by Pat Grady and Sonya Huang, partners at Sequoia Capital, to discuss their recent essay, \u201cGenerative AI: A Creative New World.\u201d\n\nThe authors delve into the potential of generative AI to enable new forms of creativity and expression, as well as the challenges and ethical considerations of this technology.\n\nGrady and Huang emphasize the potential of generative AI to revolutionize industries such as art, design and media by allowing for the creation of unique, personalized content on a scale that would be impossible for humans to achieve alone.\n\nThey also address the importance of considering the ethical implications of the technology, including the potential for biased or harmful outputs and the need for responsible use and regulation.\n\nListen to the full episode to hear more about the possibilities of generative AI and the considerations to be made as this technology moves forward.\n\nArt(ificial) Intelligence: Pindar Van Arman Builds Robots That Paint\n\nPindar Van Arman, an American artist and roboticist, designs painting robots that explore the differences between human and computational creativity. Since his first system in 2005, he has built multiple artificially creative robots. The most famous, Cloud Painter, was awarded first place at Robotart 2018.\n\nReal or Not Real? Attorney Steven Frank Uses Deep Learning to Authenticate Art\n\nSteven Frank is a partner at the law firm Morgan Lewis, specializing in intellectual property and commercial technology law. He\u2019s also half of the husband-wife team that used convolutional neural networks to authenticate artistic masterpieces, including da Vinci\u2019s Salvador Mundi , with AI\u2019s help.\n\nGANTheftAuto: Harrison Kinsley on AI-Generated Gaming Environments\n\nHumans playing games against machines is nothing new, but now computers can develop games for people to play. Programming enthusiast and social media influencer Harrison Kinsley created GANTheftAuto, an AI-based neural network that generates a playable chunk of the classic video game Grand Theft Auto V .\n\nYou can now listen to the AI Podcast through Amazon Music .\n\nAlso get the AI Podcast through Apple Music , Google Podcasts , Google Play , Castbox , DoggCatcher, Overcast , PlayerFM , Pocket Casts, Podbay , PodBean , PodCruncher, PodKicker, Soundcloud , Spotify , Stitcher and TuneIn .\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/01/18/sequoia-capital-generative-ai/\""
  },
  {
    "question": "What are some benefits of edge computing for enterprises?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDEvMDUvZGlmZmVyZW5jZS1iZXR3ZWVuLWNsb3VkLWFuZC1lZGdlLWNvbXB1dGluZy8=.pdf",
    "ground_truth_answer": "Enterprises can benefit from edge computing by experiencing lower latency, reduced cost, and improved model accuracy. Additionally, edge computing allows for wider reach, as it can process data locally without the need for internet access, extending the range of computing to previously inaccessible or remote locations.",
    "ground_truth_context": "\"\nSave time \u2013 Enterprises can lose time configuring private servers and networks. With cloud infrastructure on demand, they can deploy applications in a fraction of the time and get to market sooner.\n\nEdge computing is the practice of moving compute power physically closer to where data is generated, usually an Internet of Things device or sensor. Named for the way compute power is brought to the edge of the network or device, edge computing allows for faster data processing, increased bandwidth and ensured data sovereignty.\n\nBy processing data at a network\u2019s edge, edge computing reduces the need for large amounts of data to travel among servers, the cloud and devices or edge locations to get processed. This is particularly important for modern applications such as data science and AI.\n\nAccording to Gartner, \u201cEnterprises that have deployed edge use cases in production will grow from about 5 percent in 2019 to about 40 percent in 2024 .\u201d Many high compute applications such as deep learning and inference, data processing and analysis, simulation and video streaming have become pillars for modern life . As enterprises increasingly realize that these applications are powered by edge computing, the number of edge use cases in production should increase.\n\nEnterprises are investing in edge technologies to reap the following benefits:\n\nLower latency : Data processing at the edge results in eliminated or reduced data travel. This can accelerate insights for use cases with complex AI models that require low latency, such as fully autonomous vehicles and augmented reality.\n\nReduced cost : Using the local area network for data processing grants organizations higher bandwidth and storage at lower costs compared to cloud computing. Additionally, because processing happens at the edge, less data needs to be sent to the cloud or data center for further processing. This results in a decrease in the amount of data that needs to travel, and in the cost as well.\n\nModel accuracy : AI relies on high-accuracy models, especially for edge use cases that require real-time response. When a network\u2019s bandwidth is too low, it is typically alleviated by lowering the size of data fed into a model. This results in reduced image sizes, skipped frames in video and reduced sample rates in audio. When deployed at the edge, data feedback loops can be used to improve AI model accuracy and multiple models can be run simultaneously.\n\nWider reach : Internet access is a must for traditional cloud computing. But edge computing can process data locally, without the need for internet access. This extends the range of computing to previously inaccessible or remote locations.\""
  },
  {
    "question": "What is the name of the new AI platform by NVIDIA?",
    "document": "TlZJRElBIEFJIFdvcmtiZW5jaCBBZG9wdGlvbiA4LzgvMjMucGRm.pdf",
    "ground_truth_answer": "NVIDIA AI Workbench",
    "ground_truth_context": "\"\n\u201cAs a workstation market leader offering the performance and efficiency needed for the most demanding data science and AI models, we have a long history collaborating with NVIDIA. HP is embracing the next generation of high-performance systems, coupled with NVIDIA RTX Ada Generation GPUs and NVIDIA AI Workbench, and bringing the power of generative AI to our enterprise customers and helping move AI workloads between the cloud and locally.\u201d \u2014 Jim Nottingham, senior vice president of advanced computing solutions at HP Inc.\n\n\u201cLenovo and NVIDIA are helping customers overcome deployment complexities and more easily implement generative AI to deliver transformative services and products to the market. NVIDIA AI Workbench and the Lenovo AI-ready portfolio enable developers to leverage the power of their smart devices and scale across edge-to-cloud infrastructure.\u201d \u2014 Rob Herman, vice president and general manager of Lenovo Workstation & Client AI\n\n\u201cThe longstanding VMware and NVIDIA partnership has helped unlock the power of AI for every business by delivering an end-to-end enterprise platform optimized for AI workloads. Together, we are making generative AI more accessible and easier to implement in the enterprise. With AI Workbench, NVIDIA is giving developers a set of powerful tools to help enterprises accelerate gen AI adoption. With the new NVIDIA AI Workbench, development teams can seamlessly move AI workloads from the desktop to production.\u201d \u2014 Chris Wolf, vice president of VMware AI Labs\n\nWatch NVIDIA founder and CEO Jensen Huang\u2019s SIGGRAPH keynote address on demand to learn more about NVIDIA AI Workbench and NVIDIA AI Enterprise 4.0.\n\nAI Workbench is coming soon in early access. Sign up to get notified when it is available.\n\nAbout NVIDIA Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company\u2019s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling industrial digitalization across markets. NVIDIA is now a full-stack computing company with data- center-scale offerings that are reshaping industry. More information at https://nvidianews.nvidia.com/.\""
  },
  {
    "question": "How many genes does a minimal cell have?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDEvMjAvbGl2aW5nLWNlbGwtc2ltdWxhdGlvbi8=.pdf",
    "ground_truth_answer": "A minimal cell has around 500 genes.",
    "ground_truth_context": "\"\nNVIDIA GPUs Enable Simulation of a Living Cell Researchers from the University of Illinois at Urbana-Champaign developed GPU-accelerated software to simulate a 2-billion-atom cell that metabolizes and grows like a living cell.\n\nAuthor: Isha Salian\n\nEvery living cell contains its own bustling microcosm, with thousands of components responsible for energy production, protein building, gene transcription and more.\n\nScientists at the University of Illinois at Urbana-Champaign have built a 3D simulation that replicates these physical and chemical characteristics at a particle scale \u2014 creating a fully dynamic model that mimics the behavior of a living cell.\n\nPublished in the journal Cell , the project simulates a living minimal cell, which contains a pared-down set of genes essential for the cell\u2019s survival, function and replication. The model uses NVIDIA GPUs to simulate 7,000 genetic information processes over a 20-minute span of the cell cycle \u2013 making it what the scientists believe is the longest, most complex cell simulation to date.\n\nMinimal cells are simpler than naturally occurring ones, making them easier to recreate digitally.\n\n\u201cEven a minimal cell requires 2 billion atoms,\u201d said Zaida Luthey-Schulten, chemistry professor and co-director of the university\u2019s Center for the Physics of Living Cells. \u201cYou cannot do a 3D model like this in a realistic human time scale without GPUs.\u201d\n\nOnce further tested and refined, whole-cell models can help scientists predict how changes to the conditions or genomes of real-world cells will affect their function. But even at this stage, minimal cell simulation can give scientists insight into the physical and chemical processes that form the foundation of living cells.\n\n\u201cWhat we found is that fundamental behaviors emerge from the simulated cell \u2014 not because we programmed them in, but because we had the kinetic parameters and lipid mechanisms correct in our model,\u201d she said.\n\nLattice Microbes , the GPU-accelerated software co-developed by Luthey-Schulten and used to simulate the 3D minimal cell, is available on the NVIDIA NGC software hub.\n\nTo build the living cell model, the Illinois researchers simulated one of the simplest living cells, a parasitic bacteria called mycoplasma. They based the model on a trimmed-down version of a mycoplasma cell synthesized by scientists at J. Craig Venter Institute in La Jolla, Calif., which had just under 500 genes to keep it viable.\n\nFor comparison, a single E. coli cell has around 5,000 genes. A human cell has more than 20,000.\n\nLuthy-Schulten\u2019s team then used known properties of the mycoplasma\u2019s inner workings, including amino acids, nucleotides, lipids and small molecule metabolites to build out the model with DNA, RNA, proteins and membranes.\n\n\u201cWe had enough of the reactions that we could reproduce everything known,\u201d she said.\""
  },
  {
    "question": "Which company was recognized as the Service Delivery Partner of the Year by NVIDIA for the second consecutive year?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDQvMDQvbnZpZGlhLXBhcnRuZXItbmV0d29yay1hd2FyZHMv.pdf",
    "ground_truth_answer": "Quantiphi was recognized as the Service Delivery Partner of the Year by NVIDIA for the second consecutive year.",
    "ground_truth_context": "\"\nFedData Technology Solutions \u2014 Rising Star Partner of the Year. Recognized for NVIDIA DGX-based design wins with key federal customers and emerging work with the NVIDIA Omniverse platform for building and operating metaverse applications.\n\nInsight \u2014 Retail Partner of the Year. Recognized for its deep understanding of the industry, ecosystem partnerships and the ability to orchestrate best-in-class solutions to bring real-time speed and predictability to retailers, enabling intelligent stores , intelligent quick-service restaurants , intelligent supply chain and omni-channel management.\n\nLambda \u2014 Solution Integration Partner of the Year. Recognized for the third consecutive year for its commitment to providing end-to-end NVIDIA solutions, both on premises and in the cloud, across industries including higher education and research, the federal and public sectors, and healthcare and life sciences.\n\nMark III \u2014 Healthcare Partner of the Year. Recognized for its unique team and deep understanding of the NVIDIA portfolio, which provides academic medical centers, research institutions, healthcare systems and life sciences organizations with NVIDIA infrastructure, software and cloud technologies to build out AI, HPC and simulation Centers of Excellence.\n\nMicroway \u2014 Public Sector Partner of the Year. Recognized for its technical depth and engineering focus on servicing the public sector using technologies across the NVIDIA portfolio, including high performance computing and other specializations.\n\nQuantiphi \u2014 Service Delivery Partner of the Year. Recognized for the second consecutive year for its commitment to driving adoption of NVIDIA products in areas like generative AI services with customized large language models , digital avatars, edge computing , medical imaging and data science, as well as its expertise in helping customers build and deploy AI solutions at scale.\n\nWorld Wide Technology \u2014 AI Solution Provider of the Year. Recognized for its leadership in driving adoption of the NVIDIA portfolio of AI and accelerated computing solutions, as well as its continued investments in AI infrastructure for large language models, computer vision, Omniverse-based digital twins , and customer testing and labs in the WWT Advanced Technology Center.\n\nWorld Wide Technology \u2014 Networking Partner of the Year. Recognized for its expertise driving NVIDIA high-performance networking solutions to support accelerated computing environments across multiple industries and AI solutions.\n\nThis year\u2019s awards arrive as AI adoption is rapidly expanding across industries, unlocking new opportunities and accelerating discovery in healthcare , finance , business services and more. As AI models become more complex, the 2023 NPN Award winners are expert partners that can help enterprises develop and deploy AI in production using the infrastructure that best aligns with their operations.\n\nLearn how to join the NPN, or find your local NPN partner .\""
  },
  {
    "question": "How much data does AT&T process on average per day?",
    "document": "QVQvVCBTdXBlcmNoYXJnZXMgMy8yMS8yMy5wZGY=.pdf",
    "ground_truth_answer": "590 petabytes",
    "ground_truth_context": "\"\nAT&T Supercharges Operations With NVIDIA AI\n\nTelecoms Giant Adopts NVIDIA AI to Process Data More Efficiently, Optimize Service-Vehicle Routing, Create Digital Twins and Avatars\n\nGTC\u2014AT&T Corp. and NVIDIA today announced a collaboration in which AT&T will continue to transform its operations and enhance sustainability by using NVIDIA-powered AI for processing data, optimizing service-fleet routing and building digital avatars for employee support and training.\n\nAT&T is the first telecommunications provider to explore the use of a full suite of NVIDIA AI offerings. This includes enhancing its data processing using the NVIDIA AI Enterprise software suite, which includes the NVIDIA RAPIDS Accelerator for Apache Spark; enabling real-time vehicle routing and optimization with NVIDIA cuOpt; adopting digital avatars with NVIDIA Omniverse Avatar Cloud Engine and NVIDIA Tokkio; and utilizing conversational AI with NVIDIA Riva.\n\n\u201cWe strive each day to deliver the most efficient global network, as we drive towards net zero emissions in our operations,\u201d said Andy Markus, chief data officer at AT&T. \u201cWorking with NVIDIA to drive AI solutions across our business will help enhance experiences for both our employees and customers.\u201d\n\n\u201cIndustries are embracing a new era in which chatbots, recommendation engines and accelerated libraries for data optimization help produce AI-driven innovations,\u201d said Manuvir Das, vice president of Enterprise Computing at NVIDIA. \u201cOur work with AT&T will help the company better mine its data to drive new services and solutions for the AI-powered telco.\u201d\n\nThe Data Dilemma AT&T, which has pledged to be carbon neutral by 2035, has instituted broad initiatives to make its operations more efficient. A major challenge is optimizing energy consumption while providing network infrastructure that delivers data at high speeds.\n\nAT&T processes more than 590 petabytes of data on average a day. That is the equivalent of about 6.5 million 4K movies or more than 8x the content housed in the U.S. Library of Congress if all its collections were digitized.\n\nTelecoms aiming to reduce energy consumption face challenges across their operations. Within networks, the radio access network (RAN) consumes 73% of energy, while core network services, data centers and operations use 13%, 9% and 5%, respectively, according to the GSMA, a mobile industry trade group.\n\nAT&T first adopted NVIDIA RAPIDS Accelerator for Apache Spark to capitalize on energy-efficient GPUs across its AI and data science pipelines. This helped boost its operational efficiency across everything from training AI models and maintaining network quality and optimization, to reducing customer churn and improving fraud detection.\n\nOf the data and AI pipelines targeted with Spark-RAPIDS, AT&T saves about half of its cloud computing spend and sees faster performance, while enabling reductions in its carbon footprint.\""
  },
  {
    "question": "What is the name of the book written by Nitin Mittal and Thomas Davenport about AI?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDIvMDEvZGVsb2l0dGUtbml0aW4tbWl0dGFsLw==.pdf",
    "ground_truth_answer": "All in on AI: How Smart Companies Win Big with Artificial Intelligence.",
    "ground_truth_context": "\"\nDeloitte\u2019s Nitin Mittal on the Secrets of \u2018All-In\u2019 AI Success\n\nAuthor: Brian Caulfield\n\nArtificial intelligence is the new electricity. The fifth industrial revolution. And companies that go all-in on AI are reaping the rewards. So how do you make that happen?\n\nThat big question \u2014 how? \u2014 is explored by Nitin Mittal, principal at Deloitte, one of the world\u2019s largest professional services organizations, and co-author Thomas Davenport in their new book \u201c All in on AI: How Smart Companies Win Big with Artificial Intelligence. \u201d\n\nOn the latest episode of NVIDIA\u2019s AI Podcast , host Noah Kravitz speaks with Mittal, who leads Deloitte\u2019s artificial intelligence growth platform. He describes how companies across a wide variety of industries have used AI to radically transform their organizations and achieve competitive advantage.\n\nThe book, from the Harvard Business Review Press, explores the importance of a company-wide commitment to AI and the role of leadership in driving the adoption and implementation of the technology. Mittal emphasizes that companies must have a clear strategy and plan, and invest in the necessary technology and talent to make the most of AI.\n\nArt(ificial) Intelligence: Pindar Van Arman Builds Robots That Paint Pindar Van Arman, an American artist and roboticist, designs painting robots that explore the differences between human and computational creativity. Since his first system in 2005, he has built multiple artificially creative robots. The most famous, Cloud Painter, was awarded first place at Robotart 2018.\n\nReal or Not Real? Attorney Steven Frank Uses Deep Learning to Authenticate Art Steven Frank is a partner at the law firm Morgan Lewis, specializing in intellectual property and commercial technology law. He\u2019s also half of the husband-wife team that used convolutional neural networks to authenticate artistic masterpieces, including da Vinci\u2019s Salvador Mundi , with AI\u2019s help.\n\nGANTheftAuto: Harrison Kinsley on AI-Generated Gaming Environments Humans playing games against machines is nothing new, but now computers can develop games for people to play. Programming enthusiast and social media influencer Harrison Kinsley created GANTheftAuto, an AI-based neural network that generates a playable chunk of the classic video game Grand Theft Auto V .\n\nYou can now listen to the AI Podcast through Amazon Music , Apple Music , Google Podcasts , Google Play , Castbox , DoggCatcher, Overcast , PlayerFM , Pocket Casts, Podbay , PodBean , PodCruncher, PodKicker, Soundcloud , Spotify , Stitcher and TuneIn .\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/02/01/deloitte-nitin-mittal/\""
  },
  {
    "question": "What is the name of the platform developed by Featurespace that uses deep learning models to detect and prevent fraud?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDgvMjUvZmVhdHVyZXNwYWNlLWJsb2Nrcy1maW5hbmNpYWwtZnJhdWQv.pdf",
    "ground_truth_answer": "The platform developed by Featurespace is called ARIC Risk Hub.",
    "ground_truth_context": "\"\nFintech Company Blocks Fraud Attacks for Financial Institutions With AI and NVIDIA GPUs NVIDIA Inception member Featurespace uses AI to fight financial crime, including credit-card fraud and money laundering.\n\nAuthor: Kristen Yee\n\nE-commerce sales have skyrocketed as more people shop remotely, spurred by the pandemic. But this surge has also led fraudsters to use the opportunity to scam retailers and customers, according to David Sutton, director of analytical technology at fintech company Featurespace.\n\nThe company, headquartered in the U.K., has developed AI-powered technology to increase the speed and accuracy of fraud detection and prevention. Called ARIC Risk Hub, the platform uses deep learning models trained using NVIDIA GPUs to distinguish between valid and fraudulent transactional behavior.\n\n\u201cOnline transactions are a prime target for criminals, as they don\u2019t need to have the physical card to transact,\u201d Sutton said. \u201cWith compromised card details readily available through the dark web, fraudsters can target large volumes of cards to commit fraud with very little effort.\u201d\n\nARIC Risk Hub builds complex behavioral profiles of what it calls \u201cgenuine\u201d customers by converging transaction and third-party data from across their lifecycle within a financial institution.\n\nFraud prevention has traditionally been limited by delays in detection \u2014 with customers being notified only after money had already left their bank accounts. But ARIC Risk Hub in less than 30 milliseconds determines anomalies in even the slightest changes in a customer\u2019s behavior. It compares each financial event of a customer to their profile using AI-powered adaptive behavioral analytics.\n\nThe technology is deployed across 70 major financial institutions globally \u2014 and some have reported that it\u2019s blocked 75% of its fraud attacks, Sutton said.\n\nARIC Risk Hub helps these institutions identify criminal behavior in near-real time \u2014 reducing their financial losses and operational costs, and protecting more than 500 million consumers from fraud and financial crime.\n\nFeaturespace is a member of NVIDIA Inception , a free, global program that nurtures cutting-edge startups.\n\nFeaturespace got its start over a decade ago as a machine learning consultancy. It was rooted in the research of University of Cambridge professor Bill Fitzgerald, who was looking to make a commercial impact with adaptive behavioral analytics, a technology he created.\n\nApplied to the financial services industry, the technology quickly took flight.\n\n\u201cWith this technology, you could build a deep learning model that learns from and understands what sorts of actions a person normally takes so that it can look for changes in those actions,\u201d said Sutton.\n\nIn the past, it would take weeks for Featurespace to set up and train different deep learning models. With NVIDIA A100 Tensor Core GPUs , the company has seen up to a 100x speedup in model training, Sutton said.\""
  },
  {
    "question": "How is USD helpful for 3D artists?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDkvMjEvb21uaXZlcnNlLWJsZW5kZXItcmVsZWFzZS1vcGVudXNkLw==.pdf",
    "ground_truth_answer": "USD is helpful for 3D artists as it allows them to add physical properties to their 3D assets, ensuring that they look and behave as expected in the scenes they are placed in, and also provides interoperability between different 3D software such as Blender and Substance 3D Painter.",
    "ground_truth_context": "\"\nInto the Omniverse: Blender 4.0 Alpha Release Sets Stage for New Era of OpenUSD Artistry\n\nOpenUSD updates help bridge the 3D creativity gap, empowering artists with robust asset-export options, enhanced interoperability and more.\n\nAuthor: Dane Johnston\n\nEditor\u2019s note: This post is part of Into the Omniverse , a series focused on how artists, developers and enterprises can transform their workflows using the latest advances in OpenUSD and NVIDIA Omniverse .\n\nFor seasoned 3D artists and budding digital creation enthusiasts alike, an alpha version of the popular 3D software Blender is elevating creative journeys.\n\nWith the update\u2019s features for intricate shader network creation and enhanced asset-export capabilities, the development community using Blender and the Universal Scene Description framework, aka OpenUSD, is helping to evolve the 3D landscape.\n\nNVIDIA engineers play a key role in enhancing the OpenUSD capabilities of Blender which also brings enhancements for use with NVIDIA Omniverse , a development platform for connecting and building OpenUSD-based tools and applications.\n\nWith Blender 4.0 Alpha, 3D creators across industries and enterprises can access optimized OpenUSD workflows for various use cases.\n\nFor example, Emily Boehmer , a design intern at BMW Group\u2019s Technology Office in Munich, is using the combined power of Omniverse, Blender and Adobe Substance 3D Painter to create realistic, OpenUSD-based assets to train computer vision AI models.\n\nBoehmer worked with her team to create assets for use with SORDI.ai , an AI dataset published by BMW Group that contains over 800,000 photorealistic images.\n\nA clip of an industrial crate virtually \u201caging.\u201d\n\nUSD helped optimize Boehmer\u2019s workflow. \u201cIt\u2019s great to see USD support for both Blender and Substance 3D Painter,\u201d she said. \u201cWhen I create 3D assets using USD, I can be confident that they\u2019ll look and behave as I expect them to in the scenes that they\u2019ll be placed in because I can add physical properties to them.\u201d\n\nAustralian animator Marko Matosevic is also harnessing the combined power of Blender, Omniverse and USD in his 3D workflows.\n\nMatosevic began creating tutorials for his YouTube channel, Markom3D , to help artists of all levels. He now shares his vast 3D knowledge with over 77,000 subscribers.\n\nMost recently, Matosevic created a 3D spaceship in Blender that he later enhanced in Omniverse through virtual reality .\n\nIndividual creators aren\u2019t the only ones seeing success with Blender and USD. Multimedia entertainment studio Moment Factory creates OpenUSD-based digital twins to simulate their immersive events \u2014 including live performances, multimedia shows and interactive installations \u2014 in Omniverse with USD before deploying them in the real world.\n\nMoment Factory\u2019s interactive installation at InfoComm 2023.\""
  },
  {
    "question": "What is agent assist technology?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDQvMjcvd2hhdC1pcy1hZ2VudC1hc3Npc3Qv.pdf",
    "ground_truth_answer": "Agent assist technology uses AI and machine learning to provide facts and make real-time suggestions that help human agents across retail, telecom and other industries conduct conversations with customers.",
    "ground_truth_context": "\"\nWhat Is Agent Assist? Agent assist technology uses AI and machine learning to provide facts and make real-time suggestions that help human agents across retail, telecom and other industries conduct conversations with customers.\n\nAuthor: Angie Lee\n\n\u201cPlease hold\u201d may be the two words that customers hate most \u2014 and that contact center agents take pains to avoid saying.\n\nProviding fast, accurate, helpful responses based on contextually relevant information is key to effective customer service. It\u2019s even better if answers are personalized and take into account how a customer might be feeling.\n\nAll of this is made easier and quicker for human agents by what the industry calls agent assists.\n\nAgent assist technology uses AI and machine learning to provide facts and make real-time suggestions that help human agents across telecom, retail and other industries conduct conversations with customers.\n\nIt can integrate with contact centers\u2019 existing applications, provide faster onboarding for agents, improve the accuracy and efficiency of their responses, and increase customer satisfaction and loyalty.\n\nAgent assist technology gives human agents AI-powered information and real-time recommendations that can enhance their customer conversations.\n\nTaking conversations as input, agent assist technology outputs accurate, timely suggestions on how to best respond to queries \u2014 using a combination of automatic speech recognition (ASR) , natural language processing (NLP), machine learning and data analytics.\n\nWhile a customer speaks to a human agent, ASR tools \u2014 like the NVIDIA Riva software development kit \u2014 transcribe speech into text, in real time. The text can then be run through NLP, AI and machine learning models that offer recommendations to the human agent by analyzing different aspects of the conversation.\n\nFirst, AI models can evaluate the context of the conversation, identify topics and bring up relevant information for the human agent \u2014 like the customer\u2019s account data , a record of their previous inquiries, documents with recommended products and additional information to help resolve issues.\n\nSay a customer is looking to switch to a new phone plan. The agent assist could, for example, immediately display a chart on the human agent\u2019s screen comparing the company\u2019s offerings, which can be used as a reference throughout the conversation.\n\nAnother AI model can perform sentiment analysis based on the words a customer is using.\n\nFor example, if a customer says, \u201cI\u2019m extremely frustrated with my cellular reception,\u201d the agent assist would advise the human agent to approach the customer differently from a situation where the customer says, \u201cI am happy with my phone plan but am looking for something less expensive.\u201d\n\nIt can even present a human agent with verbiage to consider using when soothing, encouraging, informing or otherwise guiding a customer toward conflict resolution.\""
  },
  {
    "question": "What is the significance of the NSX distributed firewall running on BlueField DPUs, according to Huang?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDgvMzAvbnZpZGlhLXZtd2FyZS1uZXctZXJhLWVudGVycHJpc2UtY29tcHV0aW5nLw==.pdf",
    "ground_truth_answer": "The NSX distributed firewall running on BlueField DPUs enables every node to be more secure at virtually every touch point, realizing the zero-trust security model and providing a firewall in every single computer.",
    "ground_truth_context": "\"\nRaghuram said that customers need better performance and security in this new era.\n\nDPUs will play a crucial role in the new infrastructure architecture to accelerate performance, free up CPU cycles and provide better security.\n\n\u201cWe have rearchitected vSphere to run on DPUs,\u201d Raghuram said. This offloads software-defined infrastructure tasks like network and storage processing, he added.\n\n\u201cAnd now you get accelerated I/O, and you can have agility for developers, because all of that storage and network processing is now running in the DPU,\u201d he said.\n\nHuang explained that cloud computing and AI are driving a reinvention of data center architecture, nand that data centers are the new unit of compute.\n\nThe DPU is a new type of processor to reduce the processing burden on CPUs and provide a zero-trust security model, Huang explained.\n\nThe NVIDIA BlueField DPU , an accelerated computing platform, is designed for all enterprise workloads and optimized for NVIDIA AIn, Huang explained. The BlueField DPU offloads, accelerates and isolates the software-defined infrastructure of the data center \u2014 networking, security, storage and virtualizationn.\n\n\u201cThe return on investment \u2014 the benefits that DPU-enabled vSphere 8 with NVIDIA BlueField deliver \u2014 will be so fast because it frees up so many resources for computing that the payback is going to be instantaneous,\u201d Huang said. \u201cIt\u2019s going to be a really fantastic return.\u201d\n\nThis approach is ideal for today\u2019s security challenges. The traditional approach, Raghuram explained, is based on firewalls that focus on the network perimeter.\n\nWith the vSphere platform, VMware NSX and advancements in silicon, \u201cwe can now bring intrinsic security to life,\u201d Raghuram said.\n\nThis new approach, with the NSX distributed firewall running on BlueField DPUs, enables every node to be more secure at virtually every touch point, Huang explained, and the zero-trust security model is finally realized.\n\n\u201cAnd this is where BlueField and vSphere 8, with NSX running on BlueField, is such an incredible revolution,\u201d Huang said. \u201cWe\u2019re essentially going to have a firewall in every single computer.\u201d\n\nEnterprises can get started now. Raghuram announced the first release of vSphere on DPU is available with the vSphere 8 releasen, with ESXi and NSX support on BlueField DPUn. It lets users improve infrastructure performance by offloading and accelerating functions on the DPUn, providing more host resources to business applicationsn, Raghuram said.\n\nCertain latency- and bandwidth-sensitive workloads that previously used virtualization \u201cpass-thru\u201d can now run fully virtualized with similar performance in this new architecture, without losing key vSphere capabilities like vMotion and DRS, Raghuram said.\n\nInfrastructure admins can rely on vSphere to also manage the DPU lifecycle, thereby reducing operational overheadn, Raghuram added. And enterprises can boost infrastructure security by isolating infrastructure domains on a DPU.\""
  },
  {
    "question": "Which company announced support for cuQuantum at its launch in late 2021?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDkvMjAvY3VxdWFudHVtLXFvZGEtYWRvcHRpb24tYWNjZWxlcmF0ZXMv.pdf",
    "ground_truth_answer": "Google Quantum AI and IonQ announced support for cuQuantum at its launch in late 2021.",
    "ground_truth_context": "\"\nThe research efforts join those from existing collaborators, including Google Quantum AI and IonQ, that announced support for cuQuantum at its launch in late 2021.\n\nLearn more by watching GTC sessions that give an overview of quantum-accelerated supercomputing, its ecosystem and its applications in the pharmaceutical industry.\n\nAnd to get the big picture, watch NVIDIA founder and CEO Jensen Huang\u2019s GTC keynote below.\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/09/20/cuquantum-qoda-adoption-accelerates/\""
  },
  {
    "question": "What is the name of the new XPENG SUV launched during NVIDIA GTC?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDkvMjMveHBlbmctZzktZXYtaW5ub3ZhdGlvbi1kcml2ZS1vcmluLw==.pdf",
    "ground_truth_answer": "The new XPENG SUV launched during NVIDIA GTC is called the G9.",
    "ground_truth_context": "\"\nAn Elevated Experience: XPENG Launches G9 EV, Taking Innovation Even Higher with NVIDIA DRIVE Orin\n\nEV debut joins DRIVE ecosystem with highly advanced driver assistance system.\n\nAuthor: Danny Shapiro\n\nEditor\u2019s Note: This post has been updated to reflect the XPENG G9 launch. It was originally published in November 2021.\n\nYou don\u2019t need a private plane to be at the forefront of personal travel.\n\nElectric automaker XPENG launched the G9 SUV this week during NVIDIA GTC . The intelligent, software-defined vehicle is built on the high-performance compute of NVIDIA DRIVE Orin and delivers AI capabilities that are continuously upgraded with each over-the-air update.\n\nThe new flagship SUV debuts XPENG\u2019s centralized electronic and electrical architecture and XNGP, its latest advanced driver assistance system for a seamless driving experience. The G9 is also compatible with the next-generation superchargers for charging up to 124 miles in 5 minutes.\n\nThe XPENG G9 and its fellow EVs are elevating the driving experience with intelligent features that are always at the cutting edge.\n\nThe G9 is intelligently designed from the inside out.\n\nThe SUV is the first to be equipped with XNGP, an AI-assisted driving system that includes XPENG\u2019s City Navigation Guided Pilot, Highway Navigation Guided Pilot and Valet Parking Assist smart memory parking capabilities.\n\nIt is built on two NVIDIA DRIVE Orin systems-on-a-chip (SoC), achieving 508 trillion operations per second (TOPS). The G9 uses 31 sensors and a front-view camera for advanced object detection \u2014 its front-mounting dual-lidar sensors cover 180 degrees, reducing the size of blind spots.\n\nXNGP is capable of tackling multiple driving scenarios \u2014 regardless of map coverage \u2014 by 2023 when it is available in most cities in China.\n\nThis technology is incorporated into a centralized compute architecture for a streamlined design, powerful performance and seamless upgrades.\n\nThe G9 is designed for the international market, bringing software-defined innovation to roads around the world.\n\nIt incorporates new signature details, such as daytime running lights designed to make a sharp-eyed impression. Four daytime running lights at the top and bottom of the headlights form the XPENG logo. These headlights also include discrete lidar sensors, merging cutting-edge technology with an elegant exterior.\n\nIn addition to fast charging, the electric SUV was designed to meet global sustainability requirements as well as C-NCAP and E-NCAP five-star safety standards. Launched on September 21 in China, the G9 is expected to be delivered to customers in October 2022.\n\nThe intelligent EV joined a growing lineup of software-defined vehicles powered by NVIDIA DRIVE that are transforming the way the world moves.\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/09/23/xpeng-g9-ev-innovation-drive-orin/\""
  },
  {
    "question": "What is denoising in computer graphics?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTEvMDkvd2hhdC1pcy1kZW5vaXNpbmcv.pdf",
    "ground_truth_answer": "Denoising is a technique used to remove noise from images and renders, making them clearer and more photorealistic.",
    "ground_truth_context": "\"\nWhat Is Denoising? Denoising is an advanced technique used to decrease grainy spots and discoloration in images while minimizing the loss of quality.\n\nAuthor: JJ Kim\n\nAnyone who\u2019s taken a photo with a digital camera is likely familiar with a \u201cnoisy\u201d image: discolored spots that make the photo lose clarity and sharpness. Many photographers have tips and tricks to reduce noise in images, including fixing the settings on the camera lens or taking photos in different lighting. But it isn\u2019t just photographs that can look discolored \u2014 noise is common in computer graphics, too.\n\nNoise refers to the random variations of brightness and color that aren\u2019t part of the original image. Removing noise from imagery \u2014 which is becoming more common in the field of image processing and computer vision \u2014 is known as denoising.\n\nImage denoising uses advanced algorithms to remove noise from graphics and renders, making a huge difference to the quality of images. Photorealistic visuals and immersive renders could not be possible without denoising technology.\n\nIn computer graphics, images can be made up of both useful information and noise. The latter reduces clarity. The ideal end product of denoising would be a crisp image that only preserves the useful information. When denoising an image, it\u2019s also important to keep visual details and components such as edges, corners, textures and other sharp structures.\n\nTo reduce noise without affecting the visual details, three types of signals in an image must be targeted by denoising:\n\nDiffuse \u2014 scattered lighting reflected in all directions;\n\nSpecular or reflections \u2014 lighting reflected in a particular direction; and\n\nInfinite light-source shadows \u2014 sunlight, shadows and any other visible light source.\n\nTo create the clearest image, a user must cast thousands of rays in directions following the diffuse and specular signals. Often in real-time ray tracing, however, only one ray per pixel or even less is used.\n\nDenoising is necessary in real-time ray tracing because of the relatively low ray counts to maintain interactive performance.\n\nImage denoising is commonly based on three techniques: spatial filtering, temporal accumulation, and machine learning and deep learning reconstruction.\n\nSpatial filtering selectively alters parts of an image by reusing similar neighboring pixels. The advantage of spatial filtering is that it doesn\u2019t produce temporal lag, which is the inability to immediately respond to changing flow conditions. However, spatial filtering introduces blurriness and muddiness, as well as temporal instability, which refers to flickering and visual imperfections in the image.\n\nTemporal accumulation reuses data from the previous frame to determine if there are any artifacts \u2014 or visual anomalies \u2014 in the current frame that can be corrected. Although temporal accumulation introduces temporal lag, it doesn\u2019t produce blurriness. Instead, it adds temporal stability to reduce flickering and artifacts over multiple frames.\""
  },
  {
    "question": "What is the Array of Things (AoT) project?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDIvMjMvYWktcmVzZWFyY2hlcnMtY2xpbWF0ZS1tb2RlbGluZy1qZXRzb24v.pdf",
    "ground_truth_answer": "The Array of Things (AoT) project is an NSF-funded project led by Charlie Catlett that introduced advanced sensors and edge computing for studying urban environments. It used the Waggle edge computing platform, which was developed internally at Argonne National Laboratory.",
    "ground_truth_context": "\"\nDIY Urban AI: Researchers Drive Hyper-Local Climate Modeling Movement Northwestern University and Argonne National Laboratory are helping drive environment-focused AI models and edge computing nodes for pinpointed climate research.\n\nAuthor: Scott Martin\n\nThe do-it-yourself climate modeling movement is here.\n\nResearchers from Northwestern University and Argonne National Laboratory have been launching NVIDIA Jetson -driven edge computing Waggle devices across the globe to collect hyper-local climate information. Waggle is an open source sensor platform for edge computing developed by Argonne.\n\nWorking with this, scientists share open-source AI code designed for the edge at an app store within the Sage web portal, funded by the National Science Foundation (NSF).\n\nThe pioneering work is supporting environmental studies around the world. As a result, more and more researchers and scientists are jumping in to study climate issues with edge computing and sensors.\n\nWaggle\u2019s installed base studies everything from micro-local Chicago weather to help understand urban heat islands and their impact on residents, to climate effects on wild rice on the Ojibwe tribe\u2019s lands in Wisconsin.\n\nMore recently, the University of Oregon\u2019s Hazards Lab began using edge computing with Waggle. This work aims to help understand and identify wildfires as part of the ALERTWildfire system that provides local residents, firefighters and municipalities live data streams from smart cameras.\n\nThe efforts, on several continents, underscore the accessibility of edge computing paired with a digital infrastructure for delivering open AI models for use in these climate-related applications.\n\n\u201cMany climate models focus on large geographic scales \u2014 and therefore the impact can be difficult to understand for specific communities \u2014 but the Department of Energy wants to understand how our changing climate will impact humans, especially in an urban environment,\u201d said Pete Beckman, an Argonne distinguished fellow and co-director of the Northwestern University Argonne Institute of Science and Engineering.\n\nNVIDIA announced at GTC 2021 the Earth-2 AI supercomputer for climate research worldwide.\n\nIt all began in 2015 with an NSF project called the \u201cArray of Things,\u201d or AoT, led by Charlie Catlett, which introduced advanced sensors and edge computing for studying urban environments.\n\nThe AoT was built using the Waggle edge computing platform that had been recently developed internally at Argonne National Laboratory. Waggle brings together powerful edge AI computing like NVIDIA Jetson with industry-standard software toolkits like Kubernetes, PyTorch and TensorFlow to provide a programmable intelligent platform that can support cameras, microphones, software-defined radios, lidar and infrared imagers. To support the rapidly growing AI and sensor landscape, the NVIDIA platform was the obvious choice, offering the largest ecosystem, the most flexibility and industry-leading performance.\""
  },
  {
    "question": "What is the name of the latest season of Ubisoft's Roller Champions?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTAvMDYvZ2Vmb3JjZS1ub3ctdGh1cnNkYXktb2N0LTYv.pdf",
    "ground_truth_answer": "The latest season of Ubisoft's Roller Champions is called 'Dragon's Way'.",
    "ground_truth_context": "\"\nDakar Desert Rally captures the speed and excitement of Amaury Sport Organisation\u2019s largest rally race, with a wide variety of licensed vehicles from the world\u2019s top makers. An in-game dynamic weather system means racers will need to overcome the elements as well as the competition to win. Unique challenges and fierce, online multiplayer races are available for all members, whether an off-road simulation diehard or a casual racing fan.\n\nThis week also brings the latest season of Ubisoft\u2019s Roller Champions . \u201c Dragon\u2019s Way \u201d includes new maps, effects, cosmetics, emotes, gear and other seasonal goodies to bring out gamers\u2019 inner beasts.\n\nHere\u2019s the full list of new games coming to the cloud this week:\n\nMarauders (New release on Steam )\n\nDakar Desert Rally (New release on Steam )\n\nLord of Rigel (New release on Steam )\n\nPriest Simulator (New release on Steam )\n\nBarotrauma ( Steam )\n\nBlack Desert Online \u2013 North America and Europe ( Pearl Abyss Launcher )\n\nDon\u2019t sleep on these extra 13 titles that came to the cloud on top of the 22 games announced in September.\n\nBlind Fate: Edo no Yami ( Steam )\n\nDome Keeper ( Steam )\n\nGloomwood ( Steam )\n\nKena: Bridge of Spirits ( Steam )\n\nPotion Permit ( Steam )\n\nRealm Royale Reforged ( Epic Games Store )\n\nShatterline ( Steam )\n\nSpirit of the North ( Epic Games Store )\n\nStartup Company ( Steam )\n\nTerra Invicta ( Steam )\n\nTotal War: WARHAMMER ( Steam and Epic Games Store )\n\nTotal War: WARHAMMER II ( Steam and Epic Games Store )\n\nTotal War: WARHAMMER III ( Steam and Epic Games Store )\n\nFor some frightful fun as we enter Spooky Season, let us know what game still haunts your dreams on Twitter or in the comments below.\n\nwelcome to nnnnnn nnnnn nnn n which game still gives you nightmares? n \u2014 nn NVIDIA GeForce NOW (@NVIDIAGFN) October 5, 2022\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/10/06/geforce-now-thursday-oct-6/\""
  },
  {
    "question": "What was the percentage reduction in power consumption for servers and clients on networks running IPsec on DPUs, according to NVIDIA's test?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTEvMDMvYmx1ZWZpZWxkLWRwdXMtZW5lcmd5LWVmZmljaWVuY3kv.pdf",
    "ground_truth_answer": "21% for servers and 34% for clients",
    "ground_truth_context": "\"\nIn the tests, BlueField-2 DPUs handled virtualization, encryption and networking jobs needed to manage these portable packages of applications and code.\n\nThe DPUs slashed networking demands on CPUs by 70%, freeing them up to run other applications. What\u2019s more, they accelerated networking jobs by a whopping 54x.\n\nA technical blog provides more detail on the tests.\n\nAcross every industry, businesses are embracing a philosophy of zero trust to improve network security. So, NVIDIA tested IPsec, one of the most popular data center encryption protocols, on BlueField DPUs.\n\nThe test showed data centers could improve performance and cut power consumption 21% for servers and 34% for clients on networks running IPsec on DPUs. For large data centers, that could translate to nearly $9 million in savings on electric bills over three years.\n\nNVIDIA and its partners continue to put DPUs to the test in an expanding portfolio of use cases, but the big picture is clear.\n\n\u201cIn a world facing rising energy costs and rising demand for green IT infrastructure, the use of DPUs will become increasingly popular,\u201d the whitepaper concludes.\n\nIt\u2019s good to know the numbers, but seeing is believing. So apply to run your own test of DPUs on VMware\u2019s vSphere.\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/11/03/bluefield-dpus-energy-efficiency/\""
  },
  {
    "question": "What is the name of the social media platform where NVIDIA GeForce NOW posted a question before the weekend starts?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDgvMTAvZ2Vmb3JjZS1ub3ctdGh1cnNkYXktYXVnLTEwLw==.pdf",
    "ground_truth_answer": "The name of the social media platform is Twitter.",
    "ground_truth_context": "\"\nAnd we\u2019ve got a question before the weekend starts. Let us know how you do with the Ultimate KovvaK\u2019s challenge on Twitter or in the comments below. Whos up for a challenge? n \u2014 nn NVIDIA GeForce NOW (@NVIDIAGFN) August 9, 2023\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/08/10/geforce-now-thursday-aug-10/\""
  },
  {
    "question": "What is the name of the software toolbox developed by NVIDIA for AI researchers, data scientists, and data and machine learning operations teams?",
    "document": "TlZJRElBIEFJIFNwZWVjaCAzLzIyLzIyLnBkZg==.pdf",
    "ground_truth_answer": "The software toolbox is called NVIDIA AI.",
    "ground_truth_context": "\"\nNVIDIA AI Delivers Major Advances in Speech, Recommender System and Hyperscale Inference\n\nAmazon, Microsoft, Snap, NTT Communications Deploy NVIDIA AI; NVIDIA Riva and Merlin Enter General Availability; NVIDIA AI Enterprise 2.0 Supports All Major Data Center and Cloud Platforms; NVIDIA AI Accelerated Program Launches\n\nGTC\u2014NVIDIA today announced major updates to its NVIDIA AI platform, a suite of software for advancing such workloads as speech, recommender system, hyperscale inference and more, which has been adopted by global industry leaders such as Amazon, Microsoft, Snap and NTT Communications.\n\nThe company also announced the NVIDIA\u00ae AI Accelerated program, which helps to ensure performance and reliability of AI applications developed by NVIDIA\u2019s software and solution partners. The program increases visibility to a wide range of proven AI-accelerated applications, enabling enterprise customers to deploy with confidence on the NVIDIA AI platform. Adobe, Red Hat and VMware are among the more than 100 partners participating at launch.\n\n\u201cNVIDIA AI is the software toolbox of the world\u2019s AI community \u2014 from AI researchers and data scientists, to data and machine learning operations teams,\u201d said Jensen Huang, founder and CEO of NVIDIA. \u201cOur GTC 2022 release is massive. Whether it\u2019s creating more engaging chatbots and virtual assistants, building smarter recommendations to help consumers make better purchasing decisions, or orchestrating AI services at the largest scales, your superpowered gem is in NVIDIA AI.\u201d\n\nFreely available for developers, NVIDIA AI includes NVIDIA Riva for speech AI and NVIDIA Merlin\u2122 for smart recommendations, now both generally available. Updates have also been made across the software suite, including tools such as the NVIDIA Triton, NeMo, Maxine and TAO Toolkit.\n\nAdditionally, NVIDIA AI Enterprise 2.0 is now optimized, certified and supported across every major data center and cloud platform, including bare-metal servers, virtualized infrastructure and CPU-only systems. The suite is now supported with Red Hat OpenShift and VMware vSphere with Tanzu.\n\nSoftware Tools to Build Industry-Leading AI Applications NVIDIA AI is comprised of key enabling SDKs and tools for\u202frapid deployment, management and scaling of AI workloads across multiple nodes to power complex training and machine learning workloads. These include:\""
  },
  {
    "question": "What is the name of the blog post that NVIDIA GeForce NOW posted on August 10, 2023?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDgvMTAvZ2Vmb3JjZS1ub3ctdGh1cnNkYXktYXVnLTEwLw==.pdf",
    "ground_truth_answer": "The name of the blog post is 'GeForce NOW Thursday, Aug. 10'.",
    "ground_truth_context": "\"\nAnd we\u2019ve got a question before the weekend starts. Let us know how you do with the Ultimate KovvaK\u2019s challenge on Twitter or in the comments below. Whos up for a challenge? n \u2014 nn NVIDIA GeForce NOW (@NVIDIAGFN) August 9, 2023\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/08/10/geforce-now-thursday-aug-10/\""
  },
  {
    "question": "What is Omniverse Enterprise designed for?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDEvMDMvb21uaXZlcnNlLWVudGVycHJpc2UtcmVsZWFzZS8=.pdf",
    "ground_truth_answer": "Omniverse Enterprise is designed for maximum flexibility and scalability, allowing creators, designers, researchers, and engineers to quickly connect tools, assets, and projects to collaborate in a shared virtual space.",
    "ground_truth_context": "\"\nOmniverse Enterprise is designed for maximum flexibility and scalability. This means creators, designers, researchers and engineers can quickly connect tools, assets and projects to collaborate in a shared virtual space.\n\nOmniverse Enterprise brings updates to the core components of the platform, including:\n\nOmniverse Kit SDK , the powerful toolkit for building extensions, apps, microservices or plug-ins, now makes it easier than ever to build advanced tools and Omniverse applications with new templates and developer workflows.\n\nOmniverse Create , a reference app for composing large-scale, USD -based worlds, now includes NVIDIA DLSS 3 and multi-viewport support, making it easier for Omniverse Enterprise users to fluidly interact with extremely large and complex scenes.\n\nOmniverse View , a reference app for reviewing 3D scenes, has been streamlined to focus purely on the review and approval experience. New collaborative, real-time, interactive capabilities \u2014 including markup, annotation, measure and simple navigation \u2014 make stakeholder presentations easier and more interactive than ever.\n\nOmniverse Nucleus , the database and collaboration engine, now includes improved IT management tools, such as expanded version control to handle atomic checkpoints on the server. Updated Large File Transfer service enables users to move files between servers, on premises or in the cloud to benefit hybrid workflows. And new self-service deployment instructions for Enterprise Nucleus Server on AWS are now available, letting customers deploy and manage Nucleus in the cloud.\n\nMany customers around the world have experienced enhanced 3D workflows with Omniverse Enterprise.\n\nDentsu International, one of the largest global marketing and advertising agency networks, always looks for solutions that enable collaborative and seamless work, with a central repository for completed projects.\n\nIn addition to enhancing current pipelines with Omniverse Enterprise, Dentsu is looking to incorporate NVIDIA generative AI into its 3D design pipeline with software development kits like Omniverse ACE and Audio2Face .\n\nMercedes Benz , the German premium vehicle manufacturer, is using Omniverse Enterprise at its sites world wide to design, plan and optimize its manufacturing and assembly facilities. By developing full-fidelity digital twins of their production environments, globally dispersed teams will open up new abilities to collaborate in real time, accelerate decision-making and identify opportunities to reduce waste, decrease energy consumption and continuously enhance quality.\n\nZaha Hadid Architects (ZHA) is a renowned architectural design firm that has created some of the world\u2019s most singular building designs. ZHA focuses on creating transformative cultural, corporate and residential spaces through cutting-edge technologies. With Omniverse Enterprise, the team can accelerate and automate its workflows, as well as develop custom tools within the platform.\""
  },
  {
    "question": "What is the name of the new technology preview coming to GeForce RTX 40 Series GPUs and RTX 4080 SuperPODs?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDMvMjMvZ2Vmb3JjZS1ub3ctdGh1cnNkYXktbWFyY2gtMjMv.pdf",
    "ground_truth_answer": "The new technology preview coming to GeForce RTX 40 Series GPUs and RTX 4080 SuperPODs is Ray Tracing: Overdrive Mode.",
    "ground_truth_context": "\"\nGFN Thursday Celebrates 1,500+ Games and Their Journey to GeForce NOW GeForce NOW provides game developers with NVIDIA cloud APIs and SDKs for zero port work; plus, new RTX 4080 SuperPOD now online, five new games available to stream and a marvel-ous new reward.\n\nAuthor: GeForce NOW Community\n\nGamers love games \u2014 as do the people who make them.\n\nGeForce NOW streams over 1,500 games from the cloud, and with the Game Developers Conference in full swing this week, today\u2019s GFN Thursday celebrates all things games: the tech behind them, the tools that bring them to the cloud, the ways to play them and the new ones being added to the library this week.\n\nDevelopers use a host of NVIDIA resources to deliver the best in PC cloud gaming experiences. CD PROJEKT RED, one of many developers to tap into these resources, recently announced a new update coming to Cyberpunk 2077 on April 11 \u2014 including a new technology preview for Ray Tracing: Overdrive Mode that enables full ray tracing on GeForce RTX 40 Series GPUs and RTX 4080 SuperPODs.\n\nIn addition, members in and around Sofia, Bulgaria, can now experience the best of GeForce NOW Ultimate cloud gaming. It\u2019s the latest city to roll out RTX 4080 gaming rigs to GeForce NOW servers around the globe.\n\nPlus, with five new games joining the cloud this week, and an upcoming marvel-ous reward, GeForce NOW members can look forward to a busy weekend of streaming goodness.\n\nGDC presents the ideal time to spotlight GeForce NOW tools that enable developers to seamlessly bring their games to the cloud. NVIDIA tools, software development kits (SDKs) and partner engines together enable the production of stunning real-time content that uses AI and ray tracing. And bringing these games to billions of non-PC devices is as simple as checking an opt-in box.\n\nGeForce NOW taps into existing game stores, allowing game developers to reap the benefits of a rapidly growing audience without the hassle of developing for another platform. This means zero port work to bring games to the cloud. Users don\u2019t have to buy games for another platform and can play them on many of the devices they already own.\n\nDevelopers who want to do more have access to the GeForce NOW Developer Platform \u2014 an SDK and toolset empowering integration of, interaction with and testing on the NVIDIA cloud gaming service. It allows developers to enhance their games to run more seamlessly, add cloud gaming into their stores and launchers, and let users connect their accounts and libraries to GeForce NOW.\n\nThe SDK is a set of APIs, runtimes, samples and documentation that allows games to query for cloud execution and enable virtual touchscreens; launchers to trigger cloud streaming of a specified game; and GeForce NOW and publisher backends to facilitate account linking and game library ownership syncing, already available for Steam and Ubisoft games.\""
  },
  {
    "question": "What is the name of the upcoming Portal remaster by Nicolas 'NykO18' Grevet and David 'Kralich' Driver-Gomm?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDEvMDMvc3R1ZGlvLWxhcHRvcHMtb21uaXZlcnNlLWNlcy8=.pdf",
    "ground_truth_answer": "The upcoming Portal remaster by Nicolas 'NykO18' Grevet and David 'Kralich' Driver-Gomm is called Portal: Prelude RTX.",
    "ground_truth_context": "\"\nAnd all creators can benefit from the new fourth-generation Tensor Cores for AI tools, providing up to 2x increased performance compared to the previous generation.\n\nThe January Studio Driver, supporting the GeForce RTX 4070 Ti launch, will be available for download later this week.\n\nNVIDIA RTX GPUs unlock exclusive software for creators: Omniverse, RTX Remix, Canvas and Broadcast. They\u2019re all getting upgrades early this year.\n\nBased on the USD framework, Omniverse enables artists to connect their favorite tools from Adobe, Autodesk, Epic Games, SideFX and more. Creators can see their scenes instantly come together without lengthy import or export cycles. Changes happen in real time across the connected apps \u2014 whether a single artist is working in multiple apps simultaneously or collaborating with another artist from across the globe.\n\nThe Blender alpha branch release, part of a series of updates to Omniverse, is now available in the Omniverse Launcher. It enables users to repair geometry, generate automatic UVs and decimate high-resolution CAD data to more usable polycounts.\n\nPerformance updates to Audio2Face , Audio2Gesture and Audio2Emotion \u2014 powerful AI tools within Omniverse \u2014 better enable instant, realistic animation of characters. The AI ToyBox of experimental tools is now available in the Omniverse Extension Manager. Thousands of new, free 3D assets have also been made available worldwide for users to build and create within Omniverse.\n\nRTX Remix , which is built on Omniverse and was used to create the jaw-dropping Portal with RTX , is approaching its early-access release. Nicolas \u201cNykO18\u201d Grevet \u2014 the original creator of Portal: Prelude \u2014 is using RTX Remix to remaster his unofficial Portal prequel from 2008. Grevet is working with\n\nmodder David \u201cKralich\u201d Driver-Gomm to modernize the assets and relight the game with stunning, full ray tracing. Portal: Prelude RTX will soon become free to download from mod sites like ModDB and Nexus Mods.\n\nCanvas allows creators to paint by material, rather than color, using simple brushstrokes and AI to quickly conceptualize a beautiful image. Canvas is getting a new 360 image feature, which will become available in an upcoming free update for RTX users, helping artists create panoramic scenes and export them into any 3D app to use as an environment map. Such maps are used to change the ambient lighting of a 3D scene and appear in reflections for added realism.\n\nLater this month, Broadcast will add a new Eye Contact feature that can change the position of the subject\u2019s eyes to appear focused on the camera, as well as a new vignette effect. The update also improves the popular virtual background feature, adding temporal information for increased stability. The virtual background improvements can also be found in the recent OBS Studio 29.0 software release, and will be updated SDKs for developers later this week.\""
  },
  {
    "question": "What is NVIDIA DRIVE Concierge?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDkvMjAvZHJpdmUtY29uY2llcmdlLWFpLWV4cGVyaWVuY2Uv.pdf",
    "ground_truth_answer": "NVIDIA DRIVE Concierge is a platform that brings personalized, AI-powered safety, convenience, and entertainment features to every occupant in a vehicle.",
    "ground_truth_context": "\"\nExperience the Future of Vehicle Infotainment: NVIDIA DRIVE Concierge Brings Customized AI to Every Seat Tapping into more than a decade of infotainment experience, NVIDIA delivers personalized, intelligent, in-vehicle infotainment for every passenger.\n\nAuthor: Danny Shapiro\n\nWith NVIDIA DRIVE , in-vehicle infotainment, or IVI, is so much more than just giving directions and playing music.\n\nNVIDIA founder and CEO Jensen Huang demonstrated the capabilities of a truly IVI experience during today\u2019s GTC keynote . Using centralized, high-performance compute, the NVIDIA DRIVE Concierge platform spans traditional cockpit and cluster capabilities, as well as personalized, AI-powered safety, convenience and entertainment features for every occupant.\n\nDrivers in the U.S. spend an average of nearly 450 hours in their car every year. With just a traditional cockpit and infotainment display, those hours can seem even longer.\n\nDRIVE Concierge makes time in vehicles more enjoyable, convenient and safe, extending intelligent features to every passenger using the DRIVE AGX compute platform, DRIVE IX software stack and Omniverse Avatar Cloud Engine (ACE) .\n\nThese capabilities include crystal-clear graphics and visualizations in the cockpit and cluster, intelligent digital assistants, driver and occupant monitoring, and streaming content such as games and movies.\n\nBy running on the cross-domain DRIVE platform, DRIVE Concierge can virtualize, as well as host, multiple virtual machines on a single chip \u2014 rather than distributed computers \u2014 for streamlined development.\n\nWith this centralized architecture, DRIVE Concierge seamlessly orchestrates driver information, cockpit and infotainment functions. It supports the Android Automotive operating system, so automakers can easily customize and scale their IVI offerings.\n\nAnd digital cockpit and cluster features are just the beginning. DRIVE Concierge extends this premium functionality to the entire vehicle, with world-class confidence view, video-conferencing capabilities, digital assistants, gaming and more.\n\nSpeed, fuel range and distance traveled are key data for human drivers to be aware of. When AI is at the wheel, however, a detailed view of the vehicle\u2019s perception and planning layers is also crucial.\n\nDRIVE Concierge is tightly integrated with the DRIVE Chauffeur platform to provide high-quality, 360-degree, 4D visualization with low latency. Drivers and passengers can always see what\u2019s in the mind of the vehicle\u2019s AI, with beautiful 3D graphics.\n\nThis visualization is critical to building trust between the autonomous vehicle and its passengers, so occupants can be confident in the AV system\u2019s perception and planned path.\n\nIn addition to revolutionizing driving, AI is creating a more intelligent vehicle interior with personalized digital assistants.\n\nOmniverse ACE is a collection of cloud-based AI models and services for developers to easily build, customize and deploy interactive avatars.\""
  },
  {
    "question": "What is BERT, and who developed it?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTAvMTAvbGxtcy1haS1ob3Jpem9uLw==.pdf",
    "ground_truth_answer": "BERT (Bidirectional Encoder Representations from Transformers) is a language model developed by Google.",
    "ground_truth_context": "\"\nBeyond Words: Large Language Models Expand AI\u2019s Horizon\n\nThe powerful models making waves in natural language processing are rippling across fields from healthcare to robotics and beyond.\n\nAuthor: Rick Merritt\n\nBack in 2018, BERT got people talking about how machine learning models were learning to read and speak. Today, large language models , or LLMs, are growing up fast, showing dexterity in all sorts of applications.\n\nThey\u2019re, for one, speeding drug discovery, thanks to research from the Rostlab at Technical University of Munich, as well as work by a team from Harvard, Yale and New York University and others . In separate efforts, they applied LLMs to interpret the strings of amino acids that make up proteins, advancing our understanding of these building blocks of biology.\n\nIt\u2019s one of many inroads LLMs are making in healthcare, robotics and other fields.\n\nTransformer models \u2014 neural networks, defined in 2017, that can learn context in sequential data \u2014 got LLMs started.\n\nResearchers behind BERT and other transformer models made 2018 \u201ca watershed moment\u201d for natural language processing, a report on AI said at the end of that year. \u201cQuite a few experts have claimed that the release of BERT marks a new era in NLP,\u201d it added.\n\nDeveloped by Google, BERT (aka Bidirectional Encoder Representations from Transformers) delivered state-of-the-art scores on benchmarks for NLP. In 2019, it announced BERT powers the company\u2019s search engine.\n\nGoogle released BERT as open-source software , spawning a family of follow-ons and setting off a race to build ever larger, more powerful LLMs.\n\nFor instance, Meta created an enhanced version called RoBERTa , released as open-source code in July 2017. For training, it used \u201can order of magnitude more data than BERT,\u201d the paper said, and leapt ahead on NLP leaderboards. A scrum followed.\n\nFor convenience, score is often kept by the number of an LLM\u2019s parameters or weights, measures of the strength of a connection between two nodes in a neural network. BERT had 110 million, RoBERTa had 123 million, then BERT-Large weighed in at 354 million, setting a new record, but not for long.\n\nIn 2020, researchers at OpenAI and Johns Hopkins University announced GPT-3 , with a whopping 175 billion parameters, trained on a dataset with nearly a trillion words. It scored well on a slew of language tasks and even ciphered three-digit arithmetic.\n\n\u201cLanguage models have a wide range of beneficial applications for society,\u201d the researchers wrote.\n\nWithin weeks, people were using GPT-3 to create poems, programs, songs, websites and more. Recently, GPT-3 even wrote an academic paper about itself .\n\n\u201cI just remember being kind of blown away by the things that it could do, for being just a language model,\u201d said Percy Liang, a Stanford associate professor of computer science, speaking in a podcast .\""
  },
  {
    "question": "Which company is the world's leading manufacturer of new energy vehicles (NEVs)?",
    "document": "QllEIE5WSURJQSBEUklWRSAzLzIxLzIzLnBkZg==.pdf",
    "ground_truth_answer": "BYD",
    "ground_truth_context": "\"\nBYD, World\u2019s Largest EV Maker, Partners With NVIDIA for Mainstream Software-Defined Vehicles Built on NVIDIA DRIVE\n\nGTC\u2014NVIDIA today announced that BYD, the world\u2019s leading manufacturer of new energy vehicles (NEVs), will extend its use of the NVIDIA DRIVE Orin\u2122 centralized compute platform in a broader range of its NEVs. The enhanced partnership expands BYD\u2019s use of DRIVE Orin across the multiple models in its next-generation Dynasty and Ocean series of vehicles, bringing safe and intelligent vehicles to market.\n\n\u201cNVIDIA DRIVE Orin has been enormously successful with global mobility leaders that are building the software-defined future,\u201d said Rishi Dhall, vice president of automotive at NVIDIA. \u201cOur ongoing collaboration with BYD is a testament to the industry\u2019s confidence in DRIVE Orin as the centralized computer for today\u2019s and tomorrow\u2019s intelligent vehicles.\u201d\n\nNVIDIA and BYD share the belief that future cars will be programmable, evolving from being based on many embedded controllers to high-performance centralized computers \u2014 with functionalities delivered and enhanced through software updates over the life of the car. The compute horsepower from DRIVE Orin is critical for diverse, redundant sensor processing in real time, and provides automakers with the compute headroom to develop and support new software-driven services throughout the entire life of the vehicle.\n\nSince entering production last year, DRIVE Orin \u2014 the highest performance automotive-grade processor on the market \u2014 has become the transportation industry\u2019s AI engine of choice for the new generation of NEVs, robotaxis, shuttles and trucks. Designed to meet stringent industry safety standards, the scalable DRIVE Orin platform is capable of performing up to 254 trillion operations per second, enabling it to power AI cockpits, as well as automated driving functions \u2014 simultaneously running numerous deep neural networks to provide the ultimate safety and reliability.\n\nBeyond selecting NVIDIA DRIVE Orin for its EV fleets, BYD announced earlier this year that it is working with NVIDIA to enhance the in-vehicle experience by bringing the NVIDIA GeForce NOW\u2122 cloud gaming service to its vehicles.\n\nWith industry-leading technologies such as the Blade Battery, DM-i super hybrid technology and the e-platform, BYD has sold over 3.7 million NEVs globally as of February 2023, while creating a better mobility experience for consumers.\n\nTo learn more about the latest technology breakthroughs in automotive and other industries, watch NVIDIA founder and CEO Jensen Huang\u2019s GTC keynote. Register free for GTC to attend a number of sessions with NVIDIA and today\u2019s mobility leaders.\""
  },
  {
    "question": "How does Viaduct help vehicle and parts manufacturers?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDgvMTUvdmlhZHVjdC1kZXRlY3RpbmctdmVoaWNsZS1mYWlsdXJlLXBhdHRlcm5zLWExMDAtdHNwcC8=.pdf",
    "ground_truth_answer": "Viaduct helps vehicle and parts manufacturers reduce warranty claims and defects by detecting anomalous patterns, tracking issues, and deploying failure predictions using sensor data and time-series inference models.",
    "ground_truth_context": "\"\nQuality Control Patrol: Startup Builds Models for Detecting Vehicle Failure Patterns\n\nViaduct is helping vehicle and parts manufacturers reduce warranty claims and defects.\n\nAuthor: Scott Martin\n\nWhen it comes to preserving profit margins, data scientists for vehicle and parts manufacturers are sitting in the driver\u2019s seat.\n\nViaduct, which develops models for time-series inference, is helping enterprises harvest failure insights from the data captured on today\u2019s connected cars. It does so by tapping into sensor data and making correlations.\n\nThe four-year-old startup, based in Menlo Park, Calif., offers a platform to detect anomalous patterns, track issues, and deploy failure predictions. This enables automakers and parts suppliers to get in front of problems with real-time data to reduce warranty claims, recalls and defects, said David Hallac, the founder and CEO of Viaduct.\n\n\u201cViaduct has deployed on more than 2 million vehicles, helped avoid 500,000 hours of downtime and saved hundreds of millions of dollars in warranty costs across the industry,\u201d he said.\n\nThe company relies on NVIDIA A100 Tensor Core GPUs and the NVIDIA Time Series Prediction Platform (TSPP) framework for training, tuning and deploying time-series models, which are used to forecast data.\n\nViaduct has deployed with more than five major manufacturers of passenger cars and commercial trucks, according to the company.\n\n\u201cCustomers see it as a huge savings \u2014 the things that we are affecting are big in terms of profitability,\u201d said Hallac. \u201cIt\u2019s downtime impact, it\u2019s warranty impact and it\u2019s product development inefficiency.\u201d\n\nViaduct is a member of NVIDIA Inception , a program that provides companies with technology support and AI platforms guidance.\n\nHallac\u2019s path to Viaduct began at Stanford University. While he was a Ph.D. student there, Volkswagen came to the lab he was at with sensor data collected from more than 60 drivers over the course of several months and a research grant to explore uses.\n\nThe question the researchers delved into was how to understand the patterns and trends in the sizable body of vehicle data collected over months.\n\nThe Stanford researchers in coordination with Volkswagen Electronics Research Laboratory released a paper on the work, which highlighted Drive2Vec, a deep learning method for embedding sensor data.\n\n\u201cWe developed a bunch of algorithms focused on structural inference from high-dimensional time-series data. We were discovering useful insights, and we were able to help companies train and deploy predictive algorithms at scale,\u201d he said.\n\nViaduct handles time-series analytics with its TSI engine, which aggregates manufacturing, telematics and service data. Its model was trained with A100 GPUs tapping into NVIDIA TSPP.\n\n\u201cWe describe it as a knowledge graph \u2014 we\u2019re building this knowledge graph of all the different sensors and signals and how they correlate with each other,\u201d Hallac said.\""
  },
  {
    "question": "How did Herda use NVIDIA Omniverse in his workflow?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDgvMjMvaW4tdGhlLW52aWRpYS1zdHVkaW8tYXVndXN0LTIzLw==.pdf",
    "ground_truth_answer": "Herda used NVIDIA Omniverse to collaborate with other artists in real time and to simulate live-action camera moves and perspective inside compositing software.",
    "ground_truth_context": "\"\nHe then generated metal, stone and glass textures within the free JSplacement Classic software, then imported them back to Cinema 4D to apply them to his models. Animated elements were added to create his \u201cspace elevator\u201d with rotating disks and unfolding arms. To ensure the scene was lit identically to the original footage, Laznr used GPU-accelerated ray tracing in Otoy\u2019s Octane to create an ambient-occlusion effect, achieving photorealistic lighting with lightning speed. At this stage, Laznr imported the scene into Adobe After Effects software, then added the digital scene on top of the high-resolution video footage \u2014 creating an extraordinarily realistic visual. \u201cThe footage was in 4K RAW format, so without the capabilities of the NVIDIA RTX GPU, I wouldn\u2019t have been able to preview in real time \u2014 making me spend more time on technical parts and less on creativity,\u201d he said.\n\nMatching colors was critical, the artist added, and thankfully After Effects\u2019 several GPU-accelerated features, including Brightness & Contrast , Change Color and Exposure , helped him get the job done. Making use of his GeForce 3080 Ti GPU and ASUS ProArt NVIDIA Studio laptop, Laznr created this work of 3D art faster and more efficiently.\n\nDawid Herda, known widely as Graffit, has been an artist for more than a decade. He\u2019s most inspired by his experiences hitchhiking across his home country, Poland. Visiting Gdansk, Herda found that the architecture of the city\u2019s 600-year-old maritime crane sparked ideas for artistic transformation. He visualized the crane as a futuristic tower of metal and glass, drawing from the newer glass-fronted buildings that flank the old brick structure.\n\nHis workflow takes advantage of NVIDIA Omniverse , a platform for 3D design collaboration and world simulation, free for RTX GPU owners. The open-source, extensible Universal Scene Description file format gave Herda the freedom to work within several 3D apps at once, without having to repeatedly import and export between them. Plus, he shared his creation with fellow artists in real time, without his colleagues requiring advanced hardware.\n\n\u201cAll these features make the job of complex design much more efficient, saving me a lot of time and freeing me to focus on creativity,\u201d said Herda.\n\nHerda accessed the Omniverse Connector for Blender to accomplish 3D motion tracking, which is the simulation of live-action camera moves and perspective inside compositing software. From 4K ProRes footage of the crane captured by drone, Herda selected his favorite shots before importing them. He traced the camera movement and mapped perspective in the scene using specific points from the shots.\n\n\u201cYou often have to jump between apps, but thanks to NVIDIA Studio, everything becomes faster and smoother,\u201d Herda said.\""
  },
  {
    "question": "Where will the NVIDIA DGX Cloud infrastructure be hosted?",
    "document": "TlZJRElBIEh1Z2dpbmcgRmFjZSA4LzgvMjMucGRm.pdf",
    "ground_truth_answer": "The NVIDIA DGX Cloud infrastructure will be hosted by leading NVIDIA cloud service provider partners.",
    "ground_truth_context": "\"\nCertain statements in this press release, including, but not limited to, statements as to: the benefits, impact, performance, features and availability of our products, services and technologies, including NVIDIA DGX Cloud, NVIDIA AI computing, and NVIDIA Networking; NVIDIA\u2019s partnership with Hugging Face, including the benefits and impact thereof; researchers and developers being at the heart of generative AI that is transforming every industry; Hugging Face and NVIDIA connecting the world\u2019s largest AI community with NVIDIA\u2019s AI computing platform in the world\u2019s leading clouds, and NVIDIA AI computing being just a click away for the Hugging Face community; people around the world making new connections and discoveries with generative AI tools; DGX Cloud infrastructure being hosted by leading NVIDIA cloud service provider partners; and the availability of the NVIDIA DGX Cloud integration with Hugging Face are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing product and technologies; market acceptance of our products or our partners products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the companys website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward- looking statements to reflect future events or circumstances.\n\n\u00a9 2023 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo and NVIDIA DGX are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability and specifications are subject to change without notice.\n\nCliff Edwards NVIDIA Corporation +1-415-699-2755 cliffe@nvidia.com\""
  },
  {
    "question": "What is the name of the nonprofit organization using AI to forecast solar energy generation in the UK?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDIvMjQvYWktZm9yZWNhc3RzLXNvbGFyLWVuZXJneS11ay8=.pdf",
    "ground_truth_answer": "Open Climate Fix.",
    "ground_truth_context": "\"\nThe team is using some of the most recent deep learning models for weather modeling including MetNet, GraphCast and Deep Generative Model of Radar. They\u2019ve shown that their transformer-based AI models are 3x better at predicting solar energy generation than the forecasts generated by ESO\u2019s traditional methods. The increased precision can help ESO reach its goal of being able to operate a zero-carbon electric grid by 2025 .\n\n\u201cThe physics-based forecasting models are powerful for predicting weather on the scale of days and weeks, but take hours to produce \u2014 making them ill-suited for predictions at the hour or minute level,\u201d\n\nsaid Travers. \u201cBut with satellite images captured at intervals of a few minutes, we can get closer to a live view of cloud cover.\u201d\n\nCloud cover is of particular concern in the U.K., where cities including London, Birmingham and Glasgow receive an average of 1,400 or fewer hours of sunshine each year \u2014 less than half that of Los Angeles . But even in desert climates where cloudy days are rare, Open Climate Fix\u2019s AI models could be repurposed to detect when solar panels would be covered by dust from a sandstorm.\n\nIn addition to forecasting for the entire U.K., the nonprofit is also developing models that can forecast how much energy individual solar panels will capture. This data could help large solar farm operators understand and maximize their energy output. Smart home companies, too, could use the information to optimize energy use from solar panels on customers\u2019 roofs \u2014 giving homeowners insights about when to run power-hungry devices or schedule electric vehicle charging.\n\nOpen Climate Fix uses a cluster of NVIDIA RTX A6000 GPUs granted through an NVIDIA Hardware Grant to power its work. When training multiple models at the same time, the team shifts its overflow workload to NVIDIA A100 Tensor Core GPUs available through cloud service providers .\n\n\u201cThe hardware grants have helped us develop and iterate on our models more easily,\u201d said Jacob Bieker, a machine learning researcher at Open Climate Fix. \u201cWhen our team is first debugging and training a model, it\u2019s two or three times faster to do so locally.\u201d\n\nRead about NVIDIA\u2019s work in power and utilities and apply to join NVIDIA Inception .\n\nDiscover how AI is powering the future of clean energy .\n\nMain image of National Grid ESO Electricity National Control Center , courtesy of ESO Media Center\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/02/24/ai-forecasts-solar-energy-uk/\""
  },
  {
    "question": "What inspires Brady's artwork?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDIvMTQvaW4tdGhlLW52aWRpYS1zdHVkaW8tZmVicnVhcnktMTQv.pdf",
    "ground_truth_answer": "Brady's artwork is inspired by stop-motion animation and the ability to mix stylistic artwork with real-world limitations.",
    "ground_truth_context": "\"\nAccording to Brady, \u201c3D allows you to mix stylistic artwork with real-world limitations,\u201d which is why the touchable, cinematic look of stop-motion animation heavily inspires her work.\n\n\u201cStop-motion reforms found items into set pieces for fantastical worlds, giving them a new life and that brings me immense joy,\u201d she said.\n\nBrady composited Birth of Venus (Redux) with placeholder meshes, focusing on the central creature figure, before confirming the composition and scale were to her liking. She then sculpted finery details in the flexible 3D modeling app Foundry Modo, assisted by RTX acceleration in OTOY OctaneRender, which was made possible by her GeForce RTX 4090 GPUs.\n\nShe then applied materials and staged lighting with precision, and added speed with the RTX-accelerated ray tracing renderer. Brady has the option to deploy Octane Render, her preferred 3D renderer, in over 20 3D applications, including Autodesk 3ds Max, Blender and Maxon\u2019s Cinema 4D.\n\nAfter rendering the image, Brady deployed several post-processing features in Adobe Photoshop to help ensure the colors popped, as well as to add grain to compensate for any compression when posted on social media. Her RTX GPU affords over 30 GPU-accelerated features, such as blur gallery , object selection , liquify and smart sharpen .\n\n\u201cArt has been highly therapeutic for me, not just as an outlet to express emotion but to reflect how I see myself and what I value,\u201d Brady said. \u201cWhenever I feel overwhelmed by the pressure of expectation, whether internal or external, I redirect my efforts and instead create something that brings me joy.\u201d\n\nView more of Brady\u2019s artwork on Instagram .\n\nThe photorealistic, chocolate heart plate beside a rose-themed mug and napkins, featured below, is 3D artist and illustrator Tanja Langgner\u2019s stunning #ShareYourHeART challenge entry.\n\nLanggner gathered assets and sculpted the heart shape using McNeel Rhino and Maxon ZBrush. Next, she assembled the pieces in Blender and added textures using Adobe Substance 3D Painter. The scene was then exported from Blender as a USD file and brought into Omniverse Create, where the artist added lighting and virtual cameras to capture the sweets with the perfect illuminations and angles.\n\n\u201cThe main reason I started using Omniverse was its capability to link all my favorite apps,\u201d Langgner said. \u201cSaving time on exporting, importing and recreating materials in each app is a dream come true.\u201d\n\nLearn more about Langgner\u2019s creative journey at the upcoming Community Spotlight livestream on the Omniverse Twitch channel and YouTube on Wednesday, Feb. 22, from 11 a.m. to 12 p.m. PT.\n\nJoin the #ShareYourHeART challenge by posting your own Valentine\u2019s-themed Omniverse scene on social media using the hashtag. Entries could be featured on the NVIDIA Omniverse Twitter , LinkedIn and Instagram accounts.\n\nExperience this spring\u2019s GTC for more inspiring content, expert-led sessions and a must-see keynote to accelerate your life\u2019s creative work.\""
  },
  {
    "question": "What is the name of the CPU Superchip that offers 2x performance gains over x86 processors?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDMvMjEvZ3JhY2UtY3B1LWVuZXJneS1lZmZpY2llbmN5Lw==.pdf",
    "ground_truth_answer": "The NVIDIA Grace CPU Superchip.",
    "ground_truth_context": "\"\nGreen Light: NVIDIA Grace CPU Paves Fast Lane to Energy-Efficient Computing for Every Data Center\n\nMainstream applications get 2x gains over x86 in energy-efficient performance on microservices, analytics, simulations and more.\n\nAuthor: Ivan Goldwasser\n\nThe results are in, and they point to a new era in energy-efficient computing.\n\nIn tests of real workloads, the NVIDIA Grace CPU Superchip scored 2x performance gains over x86 processors at the same power envelope across major data center CPU applications. That opens up a whole new set of opportunities.\n\nIt means data centers can handle twice as much peak traffic. They can slash their power bills by as much as half. They can pack more punch into the confined spaces at the edge of their networks \u2014 or any combination of the above.\n\nData center managers need these options to thrive in today\u2019s era of energy efficiency .\n\nMoore\u2019s law was a brilliant predictor of the last half-century of technical progress, but today we have reached the limits of the laws of physics. Gone are the days of semiconductor capabilities doubling every 18 months; we must do more with less. Engineers can no longer pack more transistors in the same space at the same power.\n\nThat\u2019s why new x86 CPUs typically offer gains over prior generations of less than 30%. It\u2019s also why a growing number of data centers are power capped.\n\nWith the added threat of global warming, data centers don\u2019t have the luxury of expanding their power, but they still need to respond to the growing demands for computing.\n\nCompute demand is growing 10% a year in the U.S., and will double in the eight years from 2022-2030, according to a McKinsey study .\n\n\u201cPressure to make data centers sustainable is therefore high, and some regulators and governments are imposing sustainability standards on newly built data centers,\u201d it said.\n\nWith the end of Moore\u2019s law, the data center\u2019s progress in computing efficiency has stalled, according to a survey that McKinsey cited (see chart below).\n\nIn today\u2019s environment, the 2x gains NVIDIA Grace offers are the eye-popping equivalent of a multi-generational leap. It meets the requirements of today\u2019s data center executives.\n\nZac Smith \u2014 the head of edge infrastructure at Equinix, a global service provider that manages more than 240 data centers \u2014 articulated these needs in an article about energy-efficient computing.\n\n\u201cThe performance you get for the carbon impact you have is what we need to drive toward,\u201d he said.\n\n\u201cWe have 10,000 customers counting on us for help with this journey. They demand more data and more intelligence, often with AI, and they want it in a sustainable way,\u201d he added.\n\nThe Grace CPU delivers that efficient performance thanks to three innovations.\""
  },
  {
    "question": "What is the name of the cybersecurity platform developed by Booz Allen Hamilton and NVIDIA?",
    "document": "TlZJRElBIEJvb3ogQWxsZW4gSGFtaWx0b24gOS8yMC8yMi5wZGY=.pdf",
    "ground_truth_answer": "The cybersecurity platform developed by Booz Allen Hamilton and NVIDIA is called Cyber Precog.",
    "ground_truth_context": "\"\nNVIDIA and Booz Allen Hamilton Expand Partnership to Bring AI-Enabled Cybersecurity to Public and Private Sectors\n\nCompanies to Provide Services and NVIDIA AI-Accelerated Cybersecurity Platform to Analyze Massive Amounts of Data, Pinpoint Threats Faster\n\nGTC\u2014NVIDIA and Booz Allen Hamilton (NYSE: BAH) today announced an expanded collaboration to bring an AI-enabled, GPU-accelerated cybersecurity platform to customers in the public and private sectors.\n\nThe platform enables next-generation incident response systems that help customers pinpoint cybersecurity threats. It is powered by NVIDIA GPUs and NVIDIA Morpheus, the only open-source, giant-scale, GPU-accelerated AI cybersecurity processing framework.\n\nTo help customers respond to threats rapidly, Booz Allen has developed the Cyber Precog, built upon the Morpheus platform. Cyber Precog is a GPU-accelerated software platform that provides operationally honed, mission-relevant AI models and modular pipelines for rapid deployment at the edge. Cyber Precog provides the software paradigm necessary to power the Cyber Precog Flyaway Kit, a GPU-powered edge server custom designed to support cyber operations in degraded and disconnected environments.\n\nCyber Precog enables NVIDIA GPU acceleration of the kit\u2019s data ingestion at 300x the rate of CPUs, while boosting AI training by 32x and AI inference by 24x. This allows Booz Allen customers to achieve performance from a single NVIDIA GPU node that is equivalent to 135 CPU-only server nodes.\n\nBooz Allen and NVIDIA are also collaborating on next-generation solutions powered by the cybersecurity platform.\n\n\u201cTraffic moving through the modern data center continues to expand, propelled by innovations such as AI and connected devices, and it\u2019s increasingly susceptible to potential breaches and attacks,\u201d said Justin Boitano, vice president of enterprise platforms at NVIDIA. \u201cNVIDIA Morpheus enables innovators to create zero-trust technologies that detect and eliminate threats as they arise.\u201d\n\n\u201cOur customers operate in many resource-constrained environments,\u201d said Matt Tarascio, senior vice president at Booz Allen. \u201cNVIDIA GPUs, along with NVIDIA\u2019s Morpheus framework, allow us to bring enterprise capability to the edge, so that the best analytic, data processing and AI capability can be delivered to the mission. Developing Cyber Precog is one example of the many ways in which we are working rapidly to unlock advanced tradecraft, develop unique capabilities and deploy scalable solutions \u2014 all of which integrate seamlessly into our customers\u2019 missions to help them achieve cyber advantage.\u201d\""
  },
  {
    "question": "What is AIDE and what does it do?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTEvMjgvbnZpZGlhLXBhcnRuZXJzLXdpdGgtbmhzLXRydXN0cy10by1kZXBsb3ktYWktcGxhdGZvcm0taW4tdWstaG9zcGl0YWxzLw==.pdf",
    "ground_truth_answer": "AIDE is an AI platform that connects approved AI algorithms to a patient's medical record seamlessly and securely, with the data never leaving the hospital trust. It aims to improve patient care by providing clinicians with improved information about patients, making healthcare data more accessible and interoperable.",
    "ground_truth_context": "\"\nBuilt in collaboration with the AI Centre for Value Based Healthcare \u2014 a consortium of universities, hospitals and industry partners led by King\u2019s College London and Guy\u2019s and St Thomas\u2019 NHS Foundation Trust \u2014 AIDE brings the capabilities of AI to clinicians. This solution equips clinicians with improved information about patients, making healthcare data more accessible and interoperable, in order to improve patient care.\n\nThe AI Centre has already developed algorithms to improve diagnosis of COVID-19, breast cancer, brain tumor, stroke detection and dementia risk. AIDE connects approved AI algorithms to a patient\u2019s\n\nmedical record seamlessly and securely, with the data never leaving the hospital trust.\n\nOnce the clinical data has been analyzed, the results are sent back to the electronic healthcare record to support clinical decision-making. This provides another valuable data point for clinical multidisciplinary teams when reviewing patients\u2019 cases. It\u2019s hoped that AIDE can support speeding up this process to benefit patients.\n\n\u201cThe AI Centre has done invaluable work towards integrating AI into national healthcare. Deploying MONAI is a critical milestone in our journey to enable the use of safe and robot AI innovations within the clinic,\u201d said Professor Sebastien Ourselin, deputy director of the AI Centre. \u201cThis could only be achieved through our strong partnerships between academic and industry leaders like NVIDIA.\u201d\n\nAIDE was displayed in Chicago as part of the RSNA Imaging AI in Practice demonstration . The open-source code for AIDE is now published on GitHub .\n\nGet started with MONAI and watch the NVIDIA RSNA special address .\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/11/28/nvidia-partners-with-nhs-trusts-to-deploy-ai-plat form-in-uk-hospitals/\""
  },
  {
    "question": "What is the name of the fully autonomous tractor that will be on farms this year, featuring two NVIDIA Jetson GPUs for quick and accurate image classification at the edge?",
    "document": "SmV0c29uIEFHWCBPcmluIDMvMjIvMjIucGRm.pdf",
    "ground_truth_answer": "The fully autonomous tractor featuring two NVIDIA Jetson GPUs for quick and accurate image classification at the edge is the John Deere tractor.",
    "ground_truth_context": "\"\n\u201cWe are extending the powerful Microsoft Azure platform to the intelligent edge. Combining Azure\u2019s advanced capabilities with performance and software development tools such as NVIDIA Jetson AGX Orin helps give developers a seamless experience to easily build, deploy and operate production-ready AI applications.\u201d \u2014 Roanne Sones, corporate vice president, Microsoft Azure Edge + Platforms \u201cWith the global population expected to reach nearly 10 billion people by 2050, farmers have a steep challenge of feeding the world and they can\u2019t do it alone. With less available land and labor, and many variables to work through, deploying and scaling advanced technology like autonomy is key to building a continually smart, evolving and more efficient farm. Our fully autonomous tractor, featuring two NVIDIA Jetson GPUs for quick and accurate image classification at the edge, will be on farms this year, supporting farmers in overcoming challenges and providing for our growing world.\u201d \u2014 Jahmy Hindman, chief technology officer at John Deere As a recognized medical technology leader, Medtronic continues to innovate and advance solutions to improve surgical patient care. We recognize the key role for AI in digitization of surgery through quantitative analytics and real- time clinical decision support systems. The latest NVIDIA Jetson platform brings us a new level of computational performance in the operating room and enables us to advance intraoperative systems to better support surgeons, through data-enabled solutions.\u201d \u2014 Dan Stoyanov, chief scientific officer at Medtronic Digital Surgery \u201cAdvances in edge AI and robotics are reshaping entire industries by overcoming rising costs and limitations in labor and materials. Every industry will benefit from AI and robotics in the future, and 2022 is proving to be a key tipping point. Combined with NVIDIA pretrained AI models, frameworks like TAO toolkit and Isaac on Omniverse, and supported by the Jetson developer community and its partner ecosystem, Jetson AGX Orin offers a scalable AI platform with unmatched resources that make it easy to adapt to almost any application.\u201d \u2014 Jim McGregor, principal analyst at TIRIAS Research\n\nThe Jetson\u2122 embedded computing partner ecosystem encompasses a broad range of services and products, including cameras and other multimodal sensors, carrier boards, hardware design services, AI and system software, developer tools and custom software development.\n\nJetson AGX Orin Pricing and Availability The NVIDIA Jetson AGX Orin developer kit is available now at $1,999. Production modules will be available in the fourth quarter starting at $399.\n\nTo learn more about Jetson AGX Orin, watch the GTC 2022 keynote from Jensen Huang. Register for GTC for free to attend sessions with NVIDIA and industry leaders.\""
  },
  {
    "question": "What is the name of the associate director at Zaha Hadid Architects who discussed the use of NVIDIA Omniverse?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDEvMDMvb21uaXZlcnNlLWVudGVycHJpc2UtcmVsZWFzZS8=.pdf",
    "ground_truth_answer": "Shajay Bhooshan.",
    "ground_truth_context": "\"\n\u201cWe are working with NVIDIA to incorporate Omniverse as the connective infrastructure of our tech stack. Our goal is to retain design intent across the various project stages and improve productivity,\u201d said Shajay Bhooshan, associate director at Zaha Hadid Architects. \u201cWe expect NVIDIA Omniverse to play a critical, supportive role to our efforts to create a platform that\u2019s agnostic, version-controlled and a single source of truth for design data, as it evolves from idea to delivery.\u201d\n\nNVIDIA Omniverse Enterprise is available by subscription from BOXX Technologies , Dell Technologies , Z by HP and Lenovo , and channel partners including Arrow , ASK, PNY and Leadtek . The platform is optimized to run on NVIDIA-Certified, RTX-enabled desktop and mobile workstations, as well as servers, with new support for NVIDIA RTX Ada generation systems.\n\nWatch the NVIDIA special address at CES on demand. Learn more about NVIDIA Omniverse Enterprise and try Omniverse for free .\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/01/03/omniverse-enterprise-release/\""
  },
  {
    "question": "What is the name of the reference architecture developed by NVIDIA for building AI, HPC and NVIDIA Omniverse\u2122 applications?",
    "document": "TlZJRElBIFNvZnRCYW5rIDUvMjgvMjMucGRm.pdf",
    "ground_truth_answer": "NVIDIA MGX",
    "ground_truth_context": "\"\nThe solution achieves breakthrough 5G speed on an NVIDIA-accelerated 1U MGX-based server design, with industry-high throughput of 36Gbps downlink capacity, based on publicly available data on 5G accelerators. Operators have struggled to deliver such high downlink capacity using industry-standard servers.\n\nNew Reference Architecture NVIDIA MGX is a modular reference architecture that enables system manufacturers and hyperscale customers to quickly and cost-effectively build over a hundred different server variations to suit a wide range of AI, HPC and NVIDIA Omniverse\u2122 applications.\n\nBy incorporating NVIDIA Aerial\u2122 software for high-performance, software-defined, cloud-native 5G networks, these 5G base stations will allow operators to dynamically allocate compute resources, and achieve 2.5x power efficiency over competing products.\n\n\u201cThe future of generative AI requires high-performance, energy-efficient compute like that of the Arm Neoverse-based Grace Hopper Superchip from NVIDIA,\u201d said Rene Haas, CEO of Arm. \u201cCombined with NVIDIA BlueField DPUs, Grace Hopper enables the new SoftBank 5G data centers to run the most demanding compute- and memory-intensive applications and bring exponential efficiency gains to software-defined 5G and AI on Arm.\u201d\n\nAbout SoftBank Corp.\n\nGuided by the SoftBank Group\u2019s corporate philosophy, \u201cInformation Revolution \u2013 Happiness for everyone,\u201d SoftBank Corp. (TOKYO: 9434) provides telecommunications services and combines them with advanced technologies to develop and operate new businesses in Japan and globally. By fully harnessing the power of 5G, AI, IoT, Digital Twin and other key technologies, SoftBank Corp. aims to realize the \u201cImplementation of Digitalization into Society.\u201d To learn more, please visit https://www.softbank.jp/en/.\n\nAbout NVIDIA Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company\u2019s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the industrial metaverse. NVIDIA is now a full-stack computing company with data- center-scale offerings that are reshaping industry. More information at https://nvidianews.nvidia.com/.\""
  },
  {
    "question": "What is the sim-to-real gap in robotics?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDYvMjkvd2hhdC1pcy1yb2JvdGljcy1zaW11bGF0aW9uLw==.pdf",
    "ground_truth_answer": "The sim-to-real gap in robotics refers to the difference between what a robot has learned in simulation and what it needs to learn to be ready for the real world.",
    "ground_truth_context": "\"\nResearched for decades, simulations based on physics offer commercial breakthroughs today.\n\nNVIDIA PhysX , part of Omniverse core technology, delivers high-fidelity physics-based simulations, enabling real-world experimentation in virtual environments.\n\nPhysX enables development of the ability to assess grasp quality so that robots can learn to grasp unknown objects. PhysX is also highly capable for developing skills such as manipulation, locomotion and flight.\n\nLaunched into open source , PhysX 5 opens the doors for development of industrial applications everywhere. Today, roboticists can access PhysX as part of Isaac Sim, built on Omniverse.\n\nWith effective grasping enabled, based on physics, the next step was to simulate more capable robotic maneuvering applicable to industries.\n\nAssembly is a big one. It\u2019s an essential part of building products for automotive, electronics, aerospace and medical industries. Assembly tasks include tightening nuts and bolts, soldering and welding, inserting electrical connections and routing cables.\n\nRobotic assembly, however, is a long-standing work in progress. That\u2019s because the physical manipulation complexity, part variability and high accuracy and reliability requirements make it extra\n\ntricky to complete successfully \u2014 even for humans.\n\nThat hasn\u2019t stopped researchers and developers from trying, putting simulation to work in these interactions involving a lot of contact, and there are signs of progress.\n\nNVIDIA robotics and simulation researchers in 2022 came up with a novel simulation approach to overcome the robotics assemble challenge using Isaac Sim. Their research paper, titled Factory: Fast Contact for Robotic Assembly , outlines a set of physics simulation methods and robot learning tools for achieving real-time and faster simulation for a wide range of interactions requiring lots of contact, including for assembly.\n\nAdvancing the simulation work developed in the paper, researchers followed up with an effort to help solve what\u2019s called the sim-to-real gap.\n\nThis gap is the difference between what a robot has learned in simulation and what it needs to learn to be ready for the real world.\n\nIn another paper, IndustReal: Transferring Contact-Rich Assembly Tasks from Simulation to Reality , researchers outlined a set of algorithms, systems and tools for solving assembly tasks in simulation and transferring these skills to real robots.\n\nNVIDIA researchers have also developed a new, faster and more efficient method for teaching robot manipulation tasks in real life scenarios \u2014 opening drawers or dispensing soap \u2014 training significantly faster than the current standard.\n\nThe research paper RVT: Robotic View Transformer for 3D Object Manipulation uses a type of neural network called a multi-view transformer to produce virtual views from the camera input.\""
  },
  {
    "question": "What is the name of the collaboration between NVIDIA and WPP for developing a content engine powered by generative AI?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDYvMjAvY3JlYXRvcnMtc3VwZXJjaGFyZ2VkLWJ5LWdlbmVyYXRpdmUtYWktY2FubmVzLWxpb25zLw==.pdf",
    "ground_truth_answer": "NVIDIA Omniverse platform.",
    "ground_truth_context": "\"\nNVIDIA CEO: Creators Will Be \u2018Supercharged\u2019 by Generative AI NVIDIA\u2019s Jensen Huang discussed AI-enhanced creativity in a conversation with Mark Read, CEO of WPP, at the Cannes Lions Festival.\n\nAuthor: Isha Salian\n\nGenerative AI will \u201csupercharge\u201d creators across industries and content types, NVIDIA founder and CEO Jensen Huang said today at the Cannes Lions Festival, on the French Riviera.\n\n\u201cFor the very first time, the creative process can be amplified in content generation, and the content generation could be in any modality \u2014 it could be text, images, 3D, videos,\u201d Huang said in a conversation with Mark Read, CEO of WPP \u2014 the world\u2019s largest marketing and communications services company.\n\nAt the event attended by thousands of creators, marketers and brand execs from around the world, Huang outlined the impact of AI on the $700 billion digital advertising industry. He also touched on the ways AI can enhance creators\u2019 abilities, as well as the importance of responsible AI development.\n\n\u201cYou can do content generation at scale, but infinite content doesn\u2019t imply infinite creativity,\u201d he said. \u201cThrough our thoughts, we have to direct this AI to generate content that has to be aligned to your values and your brand tone.\u201d\n\nThe discussion followed Huang\u2019s recent keynote at COMPUTEX, where NVIDIA and WPP announced a collaboration to develop a content engine powered by generative AI and the NVIDIA Omniverse platform for building and operating metaverse applications.\n\nNVIDIA has been pushing the boundaries of graphics technology for 30 years and been at the forefront of the AI revolution for a decade. This combination of expertise in graphics and AI uniquely positions the company to enable the new era of generative AI applications.\n\nHuang said that \u201cthe biggest moment of modern AI\u201d can be traced back to an academic contest in 2012, when a team of University of Toronto researchers led by Alex Krizhevsky showed that NVIDIA GPUs could train an AI model that recognized objects better than any computer vision algorithm that came before it.\n\nSince then, developers have taught neural networks to recognize images, videos, speech, protein structures, physics and more.\n\n\u201cYou could learn the language of almost anything,\u201d Huang said. \u201cOnce you learn the language, you can apply the language \u2014 and the application of language is generation.\u201d\n\nGenerative AI models can create text, pixels, 3D objects and realistic motion, giving professionals superpowers to more quickly bring their ideas to life. Like a creative director working with a team of artists, users can direct AI models with prompts, and fine-tune the output to align with their vision.\n\n\u201cYou have to give the machine feedback like the best creative director,\u201d Read said.\""
  },
  {
    "question": "What is the name of the new software suite unveiled by NVIDIA for enterprise AI development?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDkvMjAvZGd4LXN5c3RlbS1zb2Z0d2FyZS1hbmQtaW5mcmFzdHJ1Y3R1cmUtdXBkYXRlcy8=.pdf",
    "ground_truth_answer": "NVIDIA AI Enterprise software suite.",
    "ground_truth_context": "\"\nNew NVIDIA DGX System Software and Infrastructure Solutions Supercharge Enterprise AI\n\nAdept AI, Hyundai Motor Group, KT and the University of Wisconsin-Madison are among the latest innovators to deliver AI built on DGX systems, Base Command and DGX SuperPOD.\n\nAuthor: Tony Paikeday\n\nAt GTC today, NVIDIA unveiled a number of updates to its DGX portfolio to power new breakthroughs in enterprise AI development.\n\nNVIDIA DGX H100 systems are now available for order. These infrastructure building blocks support NVIDIA\u2019s full-stack enterprise AI solutions.\n\nWith 32 petaflops of performance at FP8 precision, NVIDIA DGX H100 delivers a leap in efficiency for enterprise AI development. It offers 3x lower total cost of ownership and 3.5x more energy efficiency compared to the previous generation.\n\nNew NVIDIA Base Command software, which simplifies and speeds AI development, powers every DGX system \u2014 from single nodes to DGX SuperPODs.\n\nAlso unveiled was NVIDIA DGX BasePOD \u2014 the evolution of DGX POD \u2014 which makes enterprise data-center AI deployments simpler and faster for IT teams to acquire, deploy and manage.\n\nMany of the world\u2019s AI leaders are building technological breakthroughs \u2014 from self-driving cars to voice assistants \u2014 using NVIDIA DGX systems and software, and the pace of innovation is not slowing down.\n\nNVIDIA Base Command provides enterprise-grade orchestration and cluster management, and it now features a full software stack for maximizing AI developer productivity, IT manageability and workload performance.\n\nThe workflow management features of Base Command now include support for on-premises DGX SuperPOD environments, enabling businesses to gain centralized control of AI development projects with simplified collaboration for project teams, and integrated monitoring and reporting dashboards.\n\nBase Command works with the NVIDIA AI Enterprise software suite, which is now included with every DGX system. The NVIDIA AI software enables end-to-end AI development and deployment with supported AI and data science tools, optimized frameworks and pretrained models .\n\nAdditionally, it offers enterprise-workflow management and MLOps integrations with DGX-Ready Software providers Domino Data Lab , Run.ai, Weights & Biases and NVIDIA Inception member Rescale. It also includes libraries that optimize and accelerate compute, storage and network infrastructure \u2014 while ensuring maximized system uptime, security and reliability.\n\nDGX BasePOD provides a reference architecture for DGX systems that incorporates design best practices for integrating compute, networking, storage and software.\n\nCustomers are already using NVIDIA DGX POD to power the development of a broad range of enterprise applications. DGX BasePOD builds on the success of DGX POD with new industry solutions targeting the biggest AI opportunities, including natural language processing, healthcare and life sciences, and fraud detection.\""
  },
  {
    "question": "What was NVIDIA's second-quarter revenue for the Automotive sector?",
    "document": "RmluYW5jaWFsIFJlc3VsdHMgUTJGWTIzIDgvMjQvMjIucGRm.pdf",
    "ground_truth_answer": "NVIDIA's second-quarter revenue for the Automotive sector was $220 million, up 45% from a year ago and up 59% from the previous quarter.",
    "ground_truth_context": "\"\nProfessional Visualization\n\nSecond-quarter revenue was $496 million, down 4% from a year ago and down 20% from the previous quarter. Expanded its partnership with Siemens to enable the industrial metaverse and increase use of AI-driven digital twin technology. Announced Omniverse\u2122 Avatar Cloud Engine, a suite of cloud-native AI models and services that make it easier to build and customize lifelike virtual assistants and digital humans. Launched a broad initiative to evolve Universal Scene Description, the open-source and extensible language of 3D worlds, to become a foundation of the open metaverse. Announced a major release of Omniverse with new frameworks, tools, apps and plugins, including 11 new connectors to the Omniverse USD ecosystem that bring the total to 112. Co-founded the Metaverse Standards Forum to align with other members on the best ways to build the foundations of the metaverse.\n\nAutomotive\n\nSecond-quarter revenue was $220 million, up 45% from a year ago and up 59% from the previous quarter. Announced rollout plans of new model vehicles using the DRIVE Orin\u2122 compute platform by partners NIO, Li Auto, JIDU, and Human Horizons, as well as Pony.ai\u2019s use of DRIVE Orin across its line of self-driving trucks and robotaxis.\n\nCFO Commentary Commentary on the quarter by Colette Kress, NVIDIA\u2019s executive vice president and chief financial officer, is available at https://investor.nvidia.com/.\n\nConference Call and Webcast Information\n\nNVIDIA will conduct a conference call with analysts and investors to discuss its second quarter fiscal 2023 financial results and current financial prospects today at 2 p.m. Pacific time (5 p.m. Eastern time). A live webcast (listen-only mode) of the conference call will be accessible at NVIDIA\u2019s investor relations website, https://investor.nvidia.com. The webcast will be recorded and available for replay until NVIDIA\u2019s conference call to discuss its financial results for its third quarter of fiscal 2023.\""
  },
  {
    "question": "Which company has deployed its H100-powered Grand Teton AI supercomputer internally for its AI production and research teams?",
    "document": "SG9wcGVyIEdQVSBFeHBhbnNpb24gMy8yMS8yMy5wZGY=.pdf",
    "ground_truth_answer": "Meta has deployed its H100-powered Grand Teton AI supercomputer internally for its AI production and research teams.",
    "ground_truth_context": "\"\nNVIDIA Hopper GPUs Expand Reach as Demand for AI Grows\n\nNVIDIA H100 GPUs Now Being Offered by Cloud Giants to Meet Surging Demand for Generative AI Training and Inference; Meta, OpenAI, Stability AI to Leverage H100 for Next Wave of AI\n\nGTC\u2014NVIDIA and key partners today announced the availability of new products and services featuring the NVIDIA H100 Tensor Core GPU \u2014 the world\u2019s most powerful GPU for AI \u2014 to address rapidly growing demand for generative AI training and inference.\n\nOracle Cloud Infrastructure (OCI) announced the limited availability of new OCI Compute bare-metal GPU instances featuring H100 GPUs. Additionally, Amazon Web Services announced its forthcoming EC2 UltraClusters of Amazon EC2 P5 instances, which can scale in size up to 20,000 interconnected H100 GPUs. This follows Microsoft Azure\u2019s private preview announcement last week for its H100 virtual machine, ND H100 v5.\n\nAdditionally, Meta has now deployed its H100-powered Grand Teton AI supercomputer internally for its AI production and research teams.\n\nNVIDIA founder and CEO Jensen Huang announced during his GTC keynote today that NVIDIA DGX\u2122 H100 AI supercomputers are in full production and will be coming soon to enterprises worldwide.\n\n\u201cGenerative AI\u2019s incredible potential is inspiring virtually every industry to reimagine its business strategies and the technology required to achieve them,\u201d said Huang. \u201cNVIDIA and our partners are moving fast to provide the world\u2019s most powerful AI computing platform to those building applications that will fundamentally transform how we live, work and play.\u201d\n\nHopper Architecture Accelerates AI The H100, based on the NVIDIA Hopper\u2122 GPU computing architecture with its built-in Transformer Engine, is optimized for developing, training and deploying generative AI, large language models (LLMs) and recommender systems. This technology makes use of the H100\u2019s FP8 precision and offers 9x faster AI training and up to 30x faster AI inference on LLMs versus the prior-generation A100. The H100 began shipping in the fall in individual and select board units from global manufacturers.\n\nThe NVIDIA DGX H100 features eight H100 GPUs connected with NVIDIA NVLink\u00ae high-speed interconnects and integrated NVIDIA Quantum InfiniBand and Spectrum\u2122 Ethernet networking. This platform provides 32 petaflops of compute performance at FP8 precision, with 2x faster networking than the prior generation, helping maximize energy efficiency in processing large AI workloads.\n\nDGX H100 also features the complete NVIDIA AI software stack, enabling enterprises to seamlessly run and manage their AI workloads at scale. This offering includes the latest version of NVIDIA AI Enterprise, announced separately today, as well as NVIDIA Base Command\u2122, the operating system of the DGX data center, which coordinates AI training and operations across the NVIDIA DGX platform to simplify and streamline AI development.\""
  },
  {
    "question": "What is NeuralVDB?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDgvMDkvc2lnZ3JhcGgtaHVhbmctbWV0YXZlcnNlLWFpLw==.pdf",
    "ground_truth_answer": "NeuralVDB is an evolution of the open-sourced standard OpenVDB that uses neural models and GPU optimization to reduce memory requirements for simulating and rendering large and complex datasets in real time.",
    "ground_truth_context": "\"\nFidler described NVIDIA software to do just that, Instant NeRF , a tool to create a 3D object or scene from 2D images. It\u2019s the subject of one of NVIDIA\u2019s two best paper awards at SIGGRAPH.\n\nIn the other best paper award, neural graphics powers a model that can predict and reduce reaction latencies in esports and AR/VR applications. The two best papers are among 16 total that NVIDIA researchers are presenting this week at SIGGRAPH.\n\nDesigners and researchers can apply neural graphics and other techniques to create their own award-winning work using new software development kits NVIDIA unveiled at the event.\n\nFidler described one of them, Kaolin Wisp , a suite of tools to create neural fields \u2014 AI models that represent a 3D scene or object \u2014 with just a few lines of code.\n\nSeparately, NVIDIA announced NeuralVDB , the next evolution of the open-sourced standard OpenVDB that industries from visual effects to scientific computing use to simulate and render water,\n\nfire, smoke and clouds.\n\nNeuralVDB uses neural models and GPU optimization to dramatically reduce memory requirements so users can interact with extremely large and complex datasets in real time and share them more efficiently.\n\n\u201cAI, the most powerful technology force of our time, will revolutionize every field of computer science, including computer graphics, and NVIDIA RTX is the engine of neural graphics,\u201d Huang said.\n\nWatch the full special address at NVIDIA\u2019s SIGGRAPH event site . That\u2019s where you\u2019ll also find details of labs, presentations and the debut of a behind-the-scenes documentary on how we created our latest GTC keynote.\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/08/09/siggraph-huang-metaverse-ai/\""
  },
  {
    "question": "What is the name of the newsletter that provides updates on NVIDIA Studio?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDgvMDkvaW4tdGhlLW52aWRpYS1zdHVkaW8tYXVndXN0LTkv.pdf",
    "ground_truth_answer": "The NVIDIA Studio newsletter.",
    "ground_truth_context": "\"\nFollow NVIDIA Omniverse on Instagram , Medium , Twitter and YouTube for additional resources and inspiration. Check out the Omniverse forums , and join our Discord server and Twitch channel to chat with the community.\n\nFollow NVIDIA Studio on Instagram , Twitter and Facebook . Access tutorials on the Studio YouTube channel and get updates directly in your inbox by subscribing to the NVIDIA Studio newsletter .\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/08/09/in-the-nvidia-studio-august-9/\""
  },
  {
    "question": "Who created the video for The White Stripes' 'Black Math'?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDQvMjgvd2hpdGUtc3RyaXBlcy8=.pdf",
    "ground_truth_answer": "Michael Wartella created the video for The White Stripes' 'Black Math'.",
    "ground_truth_context": "\"\nRock \u2018n\u2019 Robotics: The White Stripes\u2019 AI-Assisted Visual Symphony\n\nAuthor: Brian Caulfield\n\nPlayfully blending art and technology, underground animator Michael Wartella has teamed up with artificial intelligence to breathe new life into The White Stripes\u2019 fan-favorite song, \u201cBlack Math.\u201d\n\nThe video was released earlier this month to celebrate the 20th anniversary of the groundbreaking \u201cElephant\u201d album.\n\nWartella is known for his genre-bending work as a cartoonist and animator.\n\nHis Brooklyn-based Dream Factory Animation studio produced the \u201cBlack Math\u201d video, which combines digital and practical animation techniques with AI-generated imagery.\n\n\u201cThis track is 20 years old, so we wanted to give it a fresh look, but we wanted it to look like it was cut from the same cloth as classic White Stripes videos,\u201d Wartella said.\n\nFor the \u201cBlack Math\u201d video, Wartella turned to Automatic1111, an open-source generative AI tool. To create the video, Wartella and his team started off with the actual album cover, using AI to \u201cbore\u201d into the image.\n\nThey then used AI to train the AI and build more images in a similar style. \u201cThat was really crazy and interesting and everything built from there,\u201d Wartella said.\n\nThis image-to-image deep learning model caused a sensation on its release last year, and is part of a new generation of AI tools that are transforming the arts.\n\n\u201cWe used several different AI tools and animation tools,\u201d Wartella said. \u201cFor every shot, I wanted this to look like an AI video in a way those classic CGI videos look very CGI now.\u201d\n\nWartella and his team relied heavily on archived images and video of the musician duo as well as motion-capture techniques to create a video replicating the feel of late-1990s and early-2000s music videos.\n\nWartella has long relied on NVIDIA GPUs to run a full complement of digital animation tools on workstations from Austin, Texas-based BOXX Technologies.\n\n\u201cWe\u2019ve used BOXX workstations with NVIDIA cards for almost 20 years now,\u201d he said. \u201cThat combination is just really powerful \u2014 it\u2019s fast, it\u2019s stable.\u201d\n\nWartella describes his work on the \u201cBlack Math\u201d video as a \u201ccollaboration\u201d with the AI tool, using it to generate images, tweaking the results and then returning to the technology for more.\n\n\u201cI see this as a collaboration, not just pressing a button. It\u2019s an incredibly creative tool,\u201d Wartella said of generative AI .\n\nThe results were sometimes \u201ckind of strange,\u201d a quality that Wartella prizes.\n\nHe took the output from the AI, ran it through conventional composition and editing tools, and then processed the results through AI again.\n\nWartella felt that working with AI in this way made the video stronger and more abstract.\n\nThe video presents Jack and Meg White in their 2003 personas, emerging from a whimsical, dark cyber fantasy.\n\nThe video parallels the look and feel of the band\u2019s videos from the early 2000s, even as it leans into the otherworldly, almost kaleidoscopic qualities of modern generative AI.\""
  },
  {
    "question": "What is the name of the fourth-generation DGX system that features eight H100 GPUs?",
    "document": "SG9wcGVyIDMvMjIvMjIucGRm.pdf",
    "ground_truth_answer": "The fourth-generation DGX system that features eight H100 GPUs is called DGX H100.",
    "ground_truth_context": "\"\nThe combined technology innovations of H100 extend NVIDIAs AI inference and training leadership to enable real-time and immersive applications using giant-scale AI models. The H100 will enable chatbots using the worlds most powerful monolithic transformer language model, Megatron 530B, with up to 30x higher throughput than the previous generation, while meeting the subsecond latency required for real-time conversational AI. H100 also allows researchers and developers to train massive models such as Mixture of Experts, with 395 billion parameters, up to 9x faster, reducing the training time from weeks to days.\n\nBroad NVIDIA H100 Adoption NVIDIA H100 can be deployed in every type of data center, including on-premises, cloud, hybrid-cloud and edge. It is expected to be available worldwide later this year from the worlds leading cloud service providers and computer makers, as\n\nwell as directly from NVIDIA.\n\nNVIDIAs fourth-generation DGX\u2122 system, DGX H100, features eight H100 GPUs to deliver 32 petaflops of AI performance at new FP8 precision, providing the scale to meet the massive compute requirements of large language models, recommender systems, healthcare research and climate science.\n\nEvery GPU in DGX H100 systems is connected by fourth-generation NVLink, providing 900GB/s connectivity, 1.5x more than the prior generation. NVSwitch\u2122 enables all eight of the H100 GPUs to connect over NVLink. An external NVLink Switch can network up to 32 DGX H100 nodes in the next-generation NVIDIA DGX SuperPOD\u2122 supercomputers.\n\nHopper has received broad industry support from leading cloud service providers Alibaba Cloud, Amazon Web Services, Baidu AI Cloud, Google Cloud, Microsoft Azure, Oracle Cloud and Tencent Cloud, which plan to offer H100-based instances.\n\nA wide range of servers with H100 accelerators are expected from the worlds leading systems manufacturers, including Atos, BOXX Technologies, Cisco, Dell Technologies, Fujitsu, GIGABYTE, H3C, Hewlett Packard Enterprise, Inspur, Lenovo, Nettrix and Supermicro.\n\nNVIDIA H100 at Every Scale H100 will come in SXM and PCIe form factors to support a wide range of server design requirements. A converged accelerator will also be available, pairing an H100 GPU with an NVIDIA ConnectX\u00ae-7 400Gb/s InfiniBand and Ethernet SmartNIC.\n\nNVIDIAs H100 SXM will be available in HGX\u2122 H100 server boards with four- and eight-way configurations for enterprises with applications scaling to multiple GPUs in a server and across multiple servers. HGX H100-based servers deliver the highest application performance for AI training and inference along with data analytics and HPC applications.\n\nThe H100 PCIe, with NVLink to connect two GPUs, provides more than 7x the bandwidth of PCIe 5.0, delivering outstanding performance for applications running on mainstream enterprise servers. Its form factor makes it easy to integrate into existing data center infrastructure.\""
  },
  {
    "question": "What is the name of the trademarked technology used in NVIDIA's autonomous driving solutions?",
    "document": "T21uaXZlcnNlIENsb3VkIFNlcnZpY2VzIDkvMjAvMjIucGRm.pdf",
    "ground_truth_answer": "NVIDIA's autonomous driving solutions use trademarked technology called NVIDIA Drive Sim.",
    "ground_truth_context": "\"\n\u00a9 2022 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, NVIDIA DRIVE Sim, NVIDIA HGX, NVIDIA Isaac Sim, NVIDIA Omniverse, NVIDIA OVX, and NVIDIA RTX are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated.\n\nKasia Johnston +1-415-813-8859 kasiaj@nvidia.com\""
  },
  {
    "question": "What is the name of the new supercomputer announced by NVIDIA?",
    "document": "TlZJRElBIERHWCBHSDIwMCA1LzI4LzIzLnBkZg==.pdf",
    "ground_truth_answer": "The new supercomputer announced by NVIDIA is called Helios.",
    "ground_truth_context": "\"\nCertain statements in this press release including, but not limited to, statements as to: the benefits, impact, performance, features and availability of our products, services and technologies, including NVIDIA Grace Hopper Superchips and supercomputer, NVIDIA DGX and DGX GH200, NVLink including the NVLink Switch System and NVLink interconnect technology, DGX H100, NVIDIA Grace CPU, H100 Tensor Core GPU, Helios supercomputer, Quantum-2 InfiniBand, NVIDIA Base Command and NVIDIA AI Enterprise; our collaborations with Google Cloud, Meta and Microsoft and the benefits, impact, performance, features and availability thereof; generative AI, recommender systems and data analytics being engines of the modern economy, requiring unprecedented scale, speed and efficiency; and NVIDIA\u2019s intention to provide the DGX GH200 design as a blueprint to cloud service providers and other hyperscalers so they can further customize it for their infrastructure are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing product and technologies; market acceptance of our products or our partners products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the companys website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.\n\n\u00a9 2023 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, DGX, NVIDIA Base Command, NVIDIA Grace, NVIDIA Hopper and NVLink are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability and specifications are subject to change without notice.\n\nShannon McPhee NVIDIA Corporation +1-310-920-9642 smcphee@nvidia.com\""
  },
  {
    "question": "What technology does Microsoft use to power high-quality graphics spanning large multi-display walls in their Experience Centers?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTAvMjcvcnR4LW1pY3Jvc29mdC1leHBlcmllbmNlLWNlbnRlcnMv.pdf",
    "ground_truth_answer": "Microsoft uses NVIDIA RTX A6000 GPUs, along with NVIDIA Mosaic and Quadro Sync technology, to power high-quality graphics spanning large multi-display walls in their Experience Centers.",
    "ground_truth_context": "\"\nMicrosoft Experience Centers Display Scalable, Real-Time Graphics With NVIDIA RTX and Mosaic Technology\n\nAuthor: Nicole Castro\n\nWhen customers walk into a Microsoft Experience Center in New York City, Sydney or London, they\u2019re instantly met with stunning graphics displayed on multiple screens and high-definition video walls inside a multi-story building.\n\nBuilt to showcase the latest technologies, Microsoft Experience Centers surround customers with vibrant, immersive graphics as they explore new products, watch technical demos, get hands-on experience with the latest solutions and learn more about Microsoft.\n\nTo create these engaging visual experiences in real time and on a scalable level, Microsoft sought a solution that would allow it to power high-quality graphics spanning large multi-display walls \u2014 without any gaps, artifacts or misalignment in the visuals.\n\nIt was also important that the software allowed for simplicity when managing and monitoring the display environments. Microsoft chose NVIDIA RTX A6000 GPUs , along with NVIDIA Mosaic and Quadro Sync technology, which provided support for the demanding visualizations across displays and enabled viewers to see everything as one unified visual.\n\nThe display walls in Microsoft Experience Centers feature many detailed visuals and scenes that require powerful graphics-computing performance. The HD walls display changing, detailed renders of various Microsoft products. These graphics are created with custom camera angles and fly-throughs.\n\nOnce the visuals were created, the team had to synchronize the graphics and ensure the systems were appearing in unison. In each Microsoft Experience Center, the team uses a visualization cluster of up to six systems, with a pair of RTX A6000 GPUs in each. Unreal Engine with nDisplay technology was used to make the Microsoft Video Player work in a cluster setting.\n\n\u201cNVIDIA RTX A6000 GPUs provide the smooth and powerful performance that is required to run high-quality visuals across a large number of displays,\u201d said Chris Haklitch, principal PM lead at Microsoft. \u201cThe enterprise reliability and support NVIDIA provides, along with the software and hardware only available with professional RTX GPUs, helped make our vision possible.\u201d\n\nWith NVIDIA Mosaic multi-display technology, Microsoft can treat multiple displays as a single desktop, without application software changes or visual artifacts. This enabled the walls of HD displays to be shown as a single unified visual.\n\nNVIDIA Quadro Sync II is a key technology that enables all displays to appear as a single continuous image. Designed for flexibility and scalability, Quadro Sync helps connect and synchronize the NVIDIA RTX GPUs to its attached displays.\""
  },
  {
    "question": "What is the name of the CEO of NVIDIA?",
    "document": "R2VGb3JjZSBOT1cgR2FtZXMgdG8gQ2FycyAxLzMvMjMucGRm.pdf",
    "ground_truth_answer": "The CEO of NVIDIA is Jensen Huang.",
    "ground_truth_context": "\"\nMarie Labrie Automotive +1-408-921-6987 mlabrie@nvidia.com\""
  },
  {
    "question": "What is the name of the animation AI microservice that supports 3D characters from Ready Player Me?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDEvMDMvb21uaXZlcnNlLWFjZS1lYXJseS1hY2Nlc3Mv.pdf",
    "ground_truth_answer": "The animation AI microservice that supports 3D characters from Ready Player Me is called Omniverse ACE.",
    "ground_truth_context": "\"\nEasy animation of characters, so users can bring them to life with minimal expertise.\n\nThe ability to deploy on cloud, which means avatars will be usable virtually anywhere, such as a quick-service restaurant kiosk, a tablet or a virtual-reality headset.\n\nA plug-and-play suite, built on NVIDIA Unified Compute Framework (UCF) , which enables interoperability between NVIDIA AI and other solutions, ensuring state-of-the-art AI that fits each use case.\n\nPartners such as Ready Player Me and Epic Games have experienced how Omniverse ACE can enhance workflows for AI avatars.\n\nThe Omniverse ACE animation AI microservice supports 3D characters from Ready Player Me, a platform for building cross-game avatars.\n\n\u201cDigital avatars are becoming a significant part of our daily lives. People are using avatars in games, virtual events and social apps, and even as a way to enter the metaverse,\u201d said Timmu T\u00f5ke, CEO and co-founder of Ready Player Me. \u201cWe spent seven years building the perfect avatar system, making it easy for developers to integrate in their apps and games and for users to create one avatar to explore various worlds \u2014 with NVIDIA Omniverse ACE, teams can now more easily bring these characters to life.\u201d\n\nEpic Games\u2019 advanced MetaHuman technology transformed the creation of realistic, high-fidelity digital humans. Omniverse ACE , combined with the MetaHuman framework, will make it even easier for users to design and deploy engaging 3D avatars.\n\nDigital humans don\u2019t just have to be conversational. They can be singers, as well \u2014 just like the AI avatar Toy Jensen . NVIDIA\u2019s creative team quickly created a holiday performance by TJ, using Omniverse ACE to extract the voice of a singer and turn it into TJ\u2019s voice. This enabled the avatar to sing at the same pitch and with the same rhythm as the original artist.\n\nMany creators are venturing into VTubing, a new way of livestreaming. Users embody a 2D avatar and interact with viewers. With Omniverse ACE, creators can move their avatars into 3D from 2D animation, including photos and stylistic faces. Users can render the avatars from the cloud and animate the characters from anywhere.\n\nAdditionally, the NVIDIA Tokkio reference application is expanding, with early partners building cloud-native customer service avatars for industries such as telco, banking and more.\n\nEarly access to Omniverse ACE is available to developers and teams building avatars and virtual assistants.\n\nWatch the NVIDIA special address at CES on demand . Learn more about NVIDIA Omniverse ACE and register to join the early-access program.\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/01/03/omniverse-ace-early-access/\""
  },
  {
    "question": "What is the name of the popular social media app that uses AI Green Screen and is accelerated by GeForce RTX GPUs?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDgvMjkvamFuaWNlLWpvdXJuYWwtY2FudmFzLWJsZW5kZXItdGlrdG9rLWNhcGN1dC8=.pdf",
    "ground_truth_answer": "TikTok",
    "ground_truth_context": "\"\nAdvantage AI: Elevated Creative Workflows in NVIDIA Canvas, Blender, TikTok and CapCut 3D Artist Janice.Journal creates the \u2018Eighth Wonder of the World\u2019 with AI-powered creativity this week \u2018In the NVIDIA Studio.\u2019\n\nAuthor: Gerardo Delgado\n\nEditor\u2019s note: This post is part of our weekly In the NVIDIA Studio series, which celebrates featured artists, offers creative tips and tricks and demonstrates how NVIDIA Studio technology improves creative workflows. We\u2019re also deep-diving on new GeForce RTX 40 Series GPU features, technologies and resources and how they dramatically accelerate content creation.\n\nAs beautiful and extraordinary as art forms can be, it can be easy to forget the simple joy and comforting escapism that content creation can provide for artists across creative fields.\n\nJanice K. Lee, a.k.a Janice.Journal \u2014 the subject of this week\u2019s In the NVIDIA Studio installment \u2014 is a TikTok sensation using AI to accelerate her creative process, find inspiration and automate repetitive tasks.\n\nAlso this week, NVIDIA Studio technology is powering some of the most popular mobile and desktop apps \u2014 driving creative workflows of both aspiring artists and creative professionals.\n\nWeek by week, AI becomes more ubiquitous within content creation.\n\nTake the popular social media app TikTok. All of its mobile app features, including AI Green Screen, are accelerated by GeForce RTX GPUs in the cloud. Other parts of TikTok creator workflows are also accelerated \u2014 Descript AI, a popular generative AI-powered video editing app, runs 50% faster on the latest NVIDIA L4 Tensor Core GPUs versus T4 Tensor Core GPUs .\n\nCapCut, the most widely used video editor by TikTok users, enables Simultaneous Scene Encoding, a functionality that sends independent groups of scenes to an NVIDIA Encoder (NVENC), contributing to shorter video export times without affecting image quality. This technology performs over 2x faster on NVIDIA GeForce RTX 4080 graphics cards versus on Apple\u2019s M2 Ultra.\n\nAdvanced users can move footage to their preferred desktop video editing app using native GPU-acceleration and RTX technology. This includes AV1 dual encoders ( NVIDIA GeForce RTX 4070 Ti graphics cards or higher required) for 40% better video quality for livestreamers, while video editors can slash export times nearly in half.\n\nJanice.Journal, a self-taught 3D creator, was motivated to learn new art skills as a way to cope with her busy schedule.\n\n\u201cI was going through a tough time during my junior year of college with classes and clubs,\u201d she said. \u201cWith no time to hang out with friends or decompress, my only source of comfort was learning something new every night for 20 minutes.\u201d\n\nHer passion for 3D creation quickly became evident. While Janice.Journal does consulting work during the day, she deep-dives into 3D creation at night, creating stunning scenes and tutorials to help other artists get started.\""
  },
  {
    "question": "What is NVIDIA OVX?",
    "document": "T21uaXZlcnNlIFBvcnRhbHMgVW5pdmVyc2UgMTEvMTQvMjIucGRm.pdf",
    "ground_truth_answer": "NVIDIA OVX is a computing system designed to power large-scale Omniverse digital twins, enabling fully real-time scientific and industrial digital twins for the high performance computing community.",
    "ground_truth_context": "\"\nNVIDIA Omniverse Opens Portals for Scientists to Explore Our Universe\n\n3D Simulation and Collaboration Platform Now Supports NVIDIA A100 and H100 Systems; Ecosystem Expands Into HPC With Connections to NVIDIA Modulus, NeuralVDB, and IndeX and Kitware\u2019s ParaView to Accelerate Million-X Scale Discovery\n\nSC22 -- NVIDIA today announced that NVIDIA Omniverse\u2122 \u2014 an open computing platform for building and operating metaverse applications \u2014 now connects to leading scientific computing visualization software and supports new batch- rendering workloads on systems powered by NVIDIA A100 and H100 Tensor Core GPUs.\n\nNVIDIA also introduced fully real-time scientific and industrial digital twins for the high performance computing community, enabled by NVIDIA OVX\u2122, a computing system designed to power large-scale Omniverse digital twins, and Omniverse Cloud, a software- and infrastructure-as-a-service offering.\n\nOmniverse now supports batch workloads that AI and HPC researchers, scientists and engineers can run on their existing A100 or H100 systems \u2014 including rendering videos and images or generating synthetic 3D data.\n\nTo foster more seamless, collaborative workflows for the HPC community, NVIDIA also unveiled connections to popular scientific computing tools such as Kitware\u2019s ParaView, an application for visualization; NVIDIA IndeX\u00ae for volumetric rendering; NVIDIA Modulus for developing physics-ML models; and NeuralVDB for large-scale sparse volumetric data representation.\n\n\u201cToday\u2019s scientific computing workflows are extremely complex, involving enormous datasets that are impractical to move and large, global teams that use their own specialized tools,\u201d said Dion Harris, lead product manager of accelerated computing at NVIDIA. \u201cWith new support for Omniverse on A100 and H100 systems, HPC customers can finally start to unlock legacy data silos, achieve interoperability in their complex simulation and visualization pipelines, and generate compelling visuals for their batch-rendering workflows.\u201d\n\nUsing Omniverse and hybrid-cloud workloads, scientific computing customers can connect legacy simulation and visualization pipelines to achieve distributed, fully interactive, true real-time interaction with their models and datasets. NVIDIA customers such as Argonne National Laboratory, Lockheed Martin and Princeton Plasma Physics Laboratory are already seeing benefits of Omniverse for HPC workloads.\n\nGlobal Scientific Leaders Support Omniverse Argonne National Laboratory is using NVIDIA Omniverse on its A100-powered Polaris supercomputer to connect its legacy visualization tools as a first step to developing the foundations for future digital twins.\""
  },
  {
    "question": "What is the advantage of using OpenUSD format in Toolbag?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDgvMTUvbWFybW9zZXQtdG9vbGJhZy1qaWZmeXZmeC1zdHVkaW8tbGFwdG9wcy8=.pdf",
    "ground_truth_answer": "Using OpenUSD format in Toolbag preserves physically accurate material, mesh and lighting properties, even as content travels between 3D apps such as Blender, Marmoset and Unreal Engine.",
    "ground_truth_context": "\"\nGet the latest and greatest deals on Studio laptops today.\n\nContent exported from Toolbag to Universal Scene Description (known as OpenUSD) is now fully compatible with the Omniverse ecosystem .\n\nThe OpenUSD format delivers the notable advantages of preserving physically accurate material, mesh and lighting properties, even as content travels between 3D apps such as Blender, Marmoset and Unreal Engine.\n\nRTX GPU-accelerated OptiX denoising is also available for smooth, interactive ray tracing in the viewport. Artists can now navigate in full quality without visual artifacts and performance disruptions.\n\nToolbag also integrated NVIDIA DLSS, which renders the viewport at a reduced resolution and uses sophisticated AI-based technology to upscale images, improving performance while minimizing reductions in image quality. This works especially well with high-DPI displays and is a great tool for maintaining smooth performance while working on full resolution with more complex scenes.\n\nRTX GPU-accelerated rendering gives a 2x improvement in render times and a 4x improvement in baking. DirectX 12 migration delivers an additional 25% increase in rendering and baking performance.\n\nLearn more about Toolbag 4.06 . All new users receive a full-feature, 30-day free trial license.\n\nJames Luke, a.k.a. JiffyVFX, never has to look far for inspiration.\n\n\u201cVarious films, shows, comic book characters, artists and musicians inspire me,\u201d said Luke. \u201cBut I\u2019d say the biggest inspirational factor is watching other artists\u2019 works and their behind the scenes content \u2014 I\u2019m forever watching tutorials and breakdown videos on YouTube of how other artists create their content.\u201d\n\n\u201cNVIDIA GPUs are just top-of-the-line. The support, the performance, the quality. I\u2019ve always used NVIDIA GPUs for my creative workstations over the years, and I will continue to use them for years to come.\u201d \u2014 JiffyVFX\n\nLuke\u2019s Doors to Realities series began with a simple idea: put the planet Earth outside a bedroom window using the Video Copilot\u2019s Orb plug-in for Adobe After Effects.\n\n\u201cI began seeing people post collages or montages of different aesthetics \u2014 things like cyberpunk, art deco, neo-noir, retro-futurism \u2014 wondering what it would look like to transport to one of those worlds through a portal or a door of some sort,\u201d said Luke. \u201cWhat would a first-person perspective of that look like?\u201d\n\nMore recently, Luke created a Japan-themed Doors to Realities video aided by his ASUS Zenbook Pro 14 Studio laptop , powered by a GeForce RTX 4070 GPU .\n\nLuke used 3D modeling to create the environment featured in the video. He previously used Unreal Engine for the first two installments of the series, but this time, he experimented with Kitbash 3D\u2019s Cargo app for a one-click import into Blender. It was a game-changer \u2014 finding and uploading models into Blender was never so speedy and efficient.\""
  },
  {
    "question": "When will the DLSS Frame Generation plug-ins be available to developers?",
    "document": "TmV1cmFsIEdyYXBoaWNzIERMU1MgMyAzLzE2LzIzLnBkZg==.pdf",
    "ground_truth_answer": "The DLSS Frame Generation plug-ins will be publicly available to developers during GDC, making it simpler for them to accelerate the performance of their games or applications.",
    "ground_truth_context": "\"\nCertain statements in this press release including, but not limited to, statements as to: the benefits, impact, performance and availability of our products and technologies, including NVIDIA DLSS, DLSS 3 and DLSS Frame Generation; neural graphics revolutionizing gaming since its introduction with NVIDIA DLSS; third-party games and applications supporting and integrating DLSS and DLSS 3; NVIDIA making DLSS Frame Generation plug-ins publicly available during GDC, allowing even more developers to integrate the framerate boosting technology into their games and applications; and the DLSS 3 plug-in in UE 5.2 making it simpler for any developer to accelerate the performance of their game or application are forward- looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing product and technologies; market acceptance of our products or our partners\u2019 products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the companys website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.\n\n\u00a9 2023 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, and GeForce RTX are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability and specifications are subject to change without notice.\n\nBrian Burke GameWorks NVIDIA Corp. +1-512-401-4385 bburke@nvidia.com\""
  },
  {
    "question": "What is the starting price of the Jetson Orin Nano modules?",
    "document": "SmV0c29uIE9yaW4gTmFubyA5LzIwLzIyLnBkZg==.pdf",
    "ground_truth_answer": "The starting price of the Jetson Orin Nano modules is $199.",
    "ground_truth_context": "\"\nThe Jetson Orin platform is designed to solve the toughest robotics challenges and brings accelerated computing to over 700,000 ROS developers. Combined with the powerful hardware capabilities of Orin Nano, enhancements in the latest NVIDIA Isaac\u2122 software for ROS put increased performance and productivity in the hands of roboticists.\n\nStrong Ecosystem and Software Support Jetson Orin has seen broad support across the robotics and embedded computing ecosystem, including from Canon, John Deere, Microsoft Azure, Teradyne, TK Elevator and many more.\n\nThe NVIDIA Jetson ecosystem is growing rapidly, with over 1 million developers, 6,000 customers \u2014 including 2,000 startups \u2014 and 150 partners. Jetson partners offer a wide range of support from AI software, hardware and application design services to cameras, sensors and peripherals, developer tools and development systems.\n\nOrin Nano is supported by the NVIDIA JetPack\u2122 software development kit and is powered by the same NVIDIA CUDA-X\u2122 accelerated computing stack used to create breakthrough AI products in such fields as industrial IoT, manufacturing, smart cities and more.\n\nAvailability The Jetson Orin Nano modules will be available in January, starting at $199.\n\nAbout NVIDIA Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company\u2019s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics and ignited the era of modern AI. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry. More information at https://nvidianews.nvidia.com/.\n\nCertain statements in this press release including, but not limited to, statements as to: the benefits, impact, performance,\""
  },
  {
    "question": "What is the name of the startup that is developing AI-powered enterprise search tools?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDMvMDEvZ2xlYW4tbGxtLWVudGVycHJpc2Utc2VhcmNoLw==.pdf",
    "ground_truth_answer": "Glean.",
    "ground_truth_context": "\"\nGlean Founders Talk AI-Powered Enterprise Search\n\nAuthor: Brian Caulfield\n\nThe quest for knowledge at work can feel like searching for a needle in a haystack. But what if the haystack itself could reveal where the needle is?\n\nThat\u2019s the promise of large language models , or LLMs, the subject of this week\u2019s episode of the NVIDIA AI Podcast featuring Deedy Das and Eddie Zhou, founding engineers at Silicon Valley-based startup Glean, in conversation with our host, Noah Kravitz.\n\nWith LLMs, the haystack can become a source of intelligence, helping guide knowledge workers on what they need to know.\n\nGlean is focused on providing better tools for enterprise search by indexing everything employees have access to in the company, including Slack, Confluence, GSuite and much more. The company raised a series C financing round last year, valuing the company at $1 billion.\n\nLarge language models can provide a comprehensive view of the enterprise and its data, which makes finding the information needed to get work done easier.\n\nIn the podcast, Das and Zhou discuss the challenges and opportunities of bringing LLMs into the enterprise, and how this technology can help people spend less time searching and more time working.\n\nSequoia Capital\u2019s Pat Grady and Sonya Huang on Generative AI\n\nPat Grady and Sonya Huang, partners at Sequoia Capital, to discuss their recent essay, \u201cGenerative AI: A Creative New World.\u201d The authors delve into the potential of generative AI to enable new forms of creativity and expression, as well as the challenges and ethical considerations of this technology. They also offer insights into the future of generative AI.\n\nReal or Not Real? Attorney Steven Frank Uses Deep Learning to Authenticate Art\n\nSteven Frank is a partner at the law firm Morgan Lewis, specializing in intellectual property and commercial technology law. He\u2019s also half of the husband-wife team that used convolutional neural networks to authenticate artistic masterpieces, including da Vinci\u2019s Salvador Mundi , with AI\u2019s help.\n\nGANTheftAuto: Harrison Kinsley on AI-Generated Gaming Environments\n\nHumans playing games against machines is nothing new, but now computers can develop games for people to play. Programming enthusiast and social media influencer Harrison Kinsley created GANTheftAuto, an AI-based neural network that generates a playable chunk of the classic video game Grand Theft Auto V .\n\nYou can now listen to the AI Podcast through Amazon Music , Apple Music , Google Podcasts , Google Play , Castbox , DoggCatcher, Overcast , PlayerFM , Pocket Casts, Podbay , PodBean , PodCruncher, PodKicker, Soundcloud , Spotify , Stitcher and TuneIn .\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/03/01/glean-llm-enterprise-search/\""
  },
  {
    "question": "What is the name of the company that developed the AI-equipped drones used to track rhinos?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTEvMDkvYWktZXF1aXBwZWQtZHJvbmVzLXJoaW5vcy8=.pdf",
    "ground_truth_answer": "The company that developed the AI-equipped drones used to track rhinos is NVIDIA.",
    "ground_truth_context": "\"\nMake the AI Podcast better: Have a few minutes to spare? Fill out our listener survey .\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/11/09/ai-equipped-drones-rhinos/\""
  },
  {
    "question": "What is the name of the new DGX SuperPOD AI computing platform announced by NVIDIA?",
    "document": "REdYIEgxMDAgU3lzdGVtcyAzLzIyLzIyLnBkZg==.pdf",
    "ground_truth_answer": "The new DGX SuperPOD AI computing platform announced by NVIDIA is called the NVIDIA DGX SuperPOD.",
    "ground_truth_context": "\"\nCertain statements in this press release including, but not limited to, statements as to: the benefits, impact, specifications, performance and availability of Hopper-based DGX H100 systems, NVIDIA H100 GPUs, NVIDIA DGX POD, NVIDIA DGX SuperPOD, NVIDIA Eos, NVIDIA BlueField-3 DPUs, NVIDIA ConnectX-7 Quantum-2 InfiniBand networking adapters, NVLink, NVSwitch, the NVIDIA DGX Foundry, NVIDIA Base Command software and the NVIDIA AI Enterprise software suite; AI being essential to building systems; storage from NVIDIA partners being tested and certified to meet the demands of DGX SuperPOD AI computing; MLOps applications being validated to provide DGX customers with workflow and cluster management, scheduling and orchestration solutions; customers seeking more options for adding infrastructure as enterprise AI adoption grows; Deloitte being certified to support customers; and customers\u2019 and NVIDIA channel partners\u2019 ability to upgrade and refresh existing DGX systems are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ\n\nmaterially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing product and technologies; market acceptance of our products or our partners\u2019 products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the company\u2019s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.\n\n\u00a9 2022 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, BlueField, ConnectX, DGX, NVIDIA Base Command, NVIDIA DGX POD, NVIDIA DGX SuperPOD, NVIDIA Triton Inference Server, NVLink, NVSwitch and RAPIDS are trademarks and/or registered trademarks of NVIDIA Corporation and/or Mellanox Technologies in the U.S. and other countries. All other trademarks and copyrights are the property of their respective owners. Features, pricing, availability, and specifications are subject to change without notice.\n\nShannon McPhee +1-310-920-9642 smcphee@nvidia.com\""
  },
  {
    "question": "What is the name of the AI-based neural network that generates playable chunks of Grand Theft Auto V?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDEvMDUvbmljay13YWx0b24tYWktcG9kY2FzdC8=.pdf",
    "ground_truth_answer": "GANTheftAuto",
    "ground_truth_context": "\"\n\u2018AI Dungeon\u2019 Creator Nick Walton Uses AI to Generate Infinite Gaming Storylines\n\nAuthor: Angie Lee\n\nWhat started as Nick Walton\u2019s college hackathon project grew into AI Dungeon , a popular text adventure game with over 1.5 million users.\n\nWalton is the co-founder and CEO of Latitude , a Utah-based startup that uses AI to create unique gaming storylines.\n\nHe spoke with NVIDIA AI Podcast host Noah Kravitz about how natural language processing methods can generate infinite open-ended adventure plots for interactive games like AI Dungeon, which draws an average of 150,000 new players each month.\n\nIn AI Dungeon , players type in their actions or responses to prompts \u2014 for example, \u201cYou\u2019re about to enter a world of endless possibilities, where you can do absolutely anything you can imagine \u2026 Will you proceed?\u201d \u2014 and AI keeps the story going.\n\nUnlike other text adventure games that use pre-written content, AI Dungeon offers infinite unique possibilities for each storyline, as the AI adapts and responds to almost any user input.\n\nUsers can dive into adventures individually or in multiplayer mode, which allows players with distinct characters to take turns interacting with the AI within the same game session. To kick off the story, they can choose from a list of initial prompts or create custom adventures.\n\n\u201cThere\u2019s something really compelling here in this ability to have stories that can go anywhere.\u201d \u2014 Nick Walton [3:30]\n\nIn gaming and in the world, AI enables \u201cnew experiences that are no longer static and predetermined, but dynamic and alive.\u201d \u2014 Nick Walton [7:16]\n\nGANTheftAuto: Harrison Kinsley on AI-Generated Gaming Environments\n\nHumans playing games against machines is nothing new, but now computers can develop games for people to play. Programming enthusiast and social media influencer Harrison Kinsley created GANTheftAuto, an AI-based neural network that generates a playable chunk of the classic video game Grand Theft Auto V .\n\nMatt Ginsberg Built a GPU-Powered Crossword Solver to Take on Top Word Nerds\n\nDr.Fill, the crossword puzzle-playing AI created by Matt Ginsberg \u2014 serial entrepreneur, pioneering AI researcher and former research professor \u2014 scored higher than any humans earlier this year at the American Crossword Puzzle Tournament.\n\nMaya Ackerman on LyricStudio, an AI-Based Writing Songwriting Assistant\n\nMaya Ackerman is the CEO of WaveAI, a Silicon Valley startup using AI and machine learning to, as the company motto puts it, \u201cunlock new heights of human creative expression.\u201d The startup\u2019s LyricStudio software is an AI-based lyric and poetry writing assistant.\n\nGet the AI Podcast through iTunes , Google Podcasts , Google Play , Castbox , DoggCatcher, Overcast , PlayerFM , Pocket Casts, Podbay , PodBean , PodCruncher, PodKicker, Soundcloud , Spotify , Stitcher and TuneIn . If your favorite isn\u2019t listed here, drop us a note.\n\nHave a few minutes to spare? Fill out this listener survey . Your answers will help us make a better podcast.\""
  },
  {
    "question": "What is the name of the new NVIDIA AI Workbench available in early access?",
    "document": "TlZJRElBIEdsb2JhbCBXb3Jrc3RhdGlvbiA4LzgvMjMucGRm.pdf",
    "ground_truth_answer": "NVIDIA AI Workbench",
    "ground_truth_context": "\"\nWorkstation users can also take advantage of the new NVIDIA AI Workbench, available soon in early access, which provides developers with a unified, easy-to-use toolkit for creating, fine-tuning and running generative AI models with just a few clicks. Users of any skill level can quickly create, test and customize pretrained generative AI models on a PC or workstation and then scale them to virtually any data center, public cloud or NVIDIA DGX Cloud.\n\nNext-Generation RTX Technology The new NVIDIA RTX 5000, RTX 4500 and RTX 4000 desktop GPUs feature the latest NVIDIA Ada Lovelace architecture technologies, including:\n\nNVIDIA CUDA\u00ae cores: Up to 2x the single-precision floating point throughput compared to the previous generation. Third-generation RT Cores: Up to 2x the throughput of the previous generation with the ability to concurrently run ray tracing with either shading or denoising capabilities. Fourth-generation Tensor Cores: Up to 2x faster AI training performance than the previous generation with expanded support for the FP8 data format. DLSS 3: New levels of realism and interactivity for real-time graphics with the power of AI. Larger GPU memory: The RTX 4000 provides 20GB of GDDR6 memory; the RTX 4500 offers 24GB of GDDR6 memory; and the RTX 5000 boasts 32GB of GDDR6 memory \u2014 all supporting error-code correction for error-free computing with large 3D models, rendered images, simulations and AI datasets. Extended-reality capabilities: Support for high-resolution augmented-reality and virtual-reality devices to deliver the high-performance graphics required for creating stunning AR, VR and mixed-reality content.\n\n\u201cThe NVIDIA RTX 5000 Ada GPU demonstrates NVIDIA\u2019s impressive generational performance improvements \u2014 it has significantly increased our efficiency in creating stereo panoramas using Enscape,\u201d said Dan Stine, director of design technology at architectural firm Lake|Flato. \u201cWith the performance boost and large frame buffer of RTX 5000 GPUs, our large, complex models look great in virtual reality, which gives our clients a more comfortable and contextual experience.\u201d\n\nAvailability RTX workstations featuring up to four RTX 6000 Ada GPUs, NVIDIA AI Enterprise and NVIDIA Omniverse Enterprise will be available from system builders starting in the fall.\n\nThe new NVIDIA RTX 5000 GPU is now available and shipping from HP and through global distribution partners such as Leadtek, PNY and Ryoyo Electro starting today. The NVIDIA RTX 4500 and RTX 4000 GPUs will be available in the fall from BOXX, Dell Technologies, HP and Lenovo and through global distribution partners.\""
  },
  {
    "question": "What is the name of the AI system used to search for extraterrestrial signals?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDIvMDYvYWktcG90ZW50aWFsLWFsaWVuLXNpZ25hbHMv.pdf",
    "ground_truth_answer": "The AI system used to search for extraterrestrial signals is not specified in the given text.",
    "ground_truth_context": "\"\nAI Joins Hunt for ET: Study Finds 8 Potential Alien Signals\n\nA University of Toronto undergrad among an international team of researchers unleashing deep learning in the search for extraterrestrial civilizations.\n\nAuthor: Brian Caulfield\n\nArtificial intelligence is now a part of the quest to find extraterrestrial life.\n\nResearchers have developed an AI system that outperforms traditional methods in the search for alien signals. And early results were intriguing enough to send scientists back to their radio telescopes for a second look.\n\nThe study, published last week in Nature Astronomy , highlights the crucial role that AI techniques will play in the ongoing search for extraterrestrial intelligence.\n\nThe team behind the paper trained an AI to recognize signals that natural astrophysical processes couldn\u2019t produce. They then fed it a massive dataset of over 150 terabytes of data collected by the Green Bank Telescope , one of the world\u2019s largest radio telescopes, located in West Virginia.\n\nThe AI flagged more than 20,000 signals of interest, with eight showing the tell-tale characteristics of what scientists call \u201ctechnosignatures,\u201d such as a radio signal that could tip scientists off to the existence of another civilization.\n\nIn the face of a growing deluge of data from radio telescopes, it\u2019s critical to have a fast and effective means of sorting through it all.\n\nThat\u2019s where the AI system shines.\n\nThe system was created by Peter Ma, an undergraduate student at the University of Toronto and the lead author of the paper co-authored by a constellation of experts affiliated with the University of Toronto, UC Berkeley and Breakthrough Listen , an international effort launched in 2015 to search for signs of alien civilizations.\n\nMa, who taught himself how to code, first became interested in computer science in high school. He started working on a project where he aimed to use open-source data and tackle big data problems with unanswered questions, particularly in the area of machine learning.\n\n\u201cI wanted a big science problem with open source data and big, unanswered questions,\u201d Ma says. \u201cAnd finding aliens is big.\u201d\n\nDespite initially facing some confusion and disbelief from his teachers, Ma continued to work on his project throughout high school and into his first year of college, where he reached out to others and found support from researchers at the University of Toronto, UC Berkeley and Breakthrough Listen to identify signals from extraterrestrial civilizations.\n\nThe paper describes a two-step AI method to classify signals as either radio interference or a potential technosignature.\n\nThe first step uses an autoencoder to identify salient features in the data. This system, built using the TensorFlow API , was accelerated by four NVIDIA TITAN X GPUs at UC Berkeley.\n\nThe second step feeds those features to a random forest classifier , which decides whether a signal is noteworthy or just interference.\""
  },
  {
    "question": "What is NVIDIA DRIVE Concierge?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDkvMjAvZHJpdmUtY29uY2llcmdlLWFpLWV4cGVyaWVuY2Uv.pdf",
    "ground_truth_answer": "NVIDIA DRIVE Concierge is a software-defined capability that allows passengers to watch videos, experience high-performance gaming, and access their favorite apps and stream videos and games on any vehicle screen.",
    "ground_truth_context": "\"\nWith ACE, AV developers can create in-vehicle assistants that are easily customizable with speech AI, computer vision, natural language understanding, recommendation engines and simulation technologies.\n\nThese avatars can help make recommendations, book reservations, access vehicle controls and provide alerts for situations like if a valuable item is left behind.\n\nWith software-defined capabilities, cars are becoming living spaces, complete with the same entertainment available at home.\n\nNVIDIA DRIVE Concierge lets passengers watch videos and experience high-performance gaming wherever they go. Users can choose from their favorite apps and stream videos and games on any vehicle screen.\n\nBy using the NVIDIA GeForce NOW cloud gaming service, passengers can access more than 1,400 titles without the need for downloads, benefitting from automatic updates and unlimited cloud storage.\n\nIntelligent interiors provide an added layer of safety to vehicles, in addition to convenience and entertainment.\n\nDRIVE Concierge uses interior sensors and dedicated deep neural networks for driver monitoring, which ensures attention is on the road in situations where the human is in control.\n\nIt can also perform passenger monitoring to make sure that occupants are safe and no precious cargo is left behind.\n\nUsing NVIDIA DRIVE Sim on Omniverse , developers can collaborate to design passenger interactions with such cutting-edge features in the vehicle.\n\nBy tapping into NVIDIA\u2019s past heritage of infotainment technology, DRIVE Concierge is revolutionizing the future of in-vehicle experiences.\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/09/20/drive-concierge-ai-experience/\""
  },
  {
    "question": "What is the name of the superchip that runs the full stack of NVIDIA AI software for recommender systems?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDkvMjAvZ3JhY2UtaG9wcGVyLXJlY29tbWVuZGVyLXN5c3RlbXMv.pdf",
    "ground_truth_answer": "The Grace Hopper Superchip.",
    "ground_truth_context": "\"\nThe overall result is recommenders get a further up to 4x more performance and greater efficiency using Grace Hopper than using Hopper with traditional CPUs (see chart below).\n\nThe Grace Hopper Superchip runs the full stack of NVIDIA AI software used in some of the world\u2019s largest recommender systems today.\n\nNVIDIA Merlin is the rocket fuel of recommenders, a collection of models, methods and libraries for building AI systems that can provide better predictions and increase clicks.\n\nNVIDIA Merlin HugeCTR , a recommender framework, helps users process massive datasets fast across distributed GPU clusters with help from the NVIDIA Collective Communications Library .\n\nLearn more about Grace Hopper and NVLink in this technical blog . Watch this GTC session to learn more about building recommender systems.\n\nYou can also hear NVIDIA CEO and co-founder Jensen Huang provide perspective on recommenders here or watch the full GTC keynote below.\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/09/20/grace-hopper-recommender-systems/\""
  },
  {
    "question": "What is the name of the weather prediction model developed by NVIDIA?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDcvMDUvYWktZWZmaWNpZW50LXdlYXRoZXItcHJlZGljdGlvbnMv.pdf",
    "ground_truth_answer": "FourCastNet.",
    "ground_truth_context": "\"\nA Change in the Weather: AI, Accelerated Computing Promise Faster, More Efficient Predictions These technologies provide the much-needed capability of speeding up and refining weather prediction and climate modeling, while enhancing energy efficiency.\n\nAuthor: Harry Petty\n\nThe increased frequency and severity of extreme weather and climate events could take a million lives and cost $1.7 trillion annually by 2050, according to the Munich Reinsurance Company .\n\nThis underscores a critical need for accurate weather forecasting, especially with the rise in severe weather occurrences such as blizzards, hurricanes and heatwaves. AI and accelerated computing are poised to help.\n\nMore than 180 weather modeling centers employ robust high performance computing ( HPC) infrastructure to crunch traditional numerical weather prediction (NWP) models. These include the European Center for Medium-Range Weather Forecasts (ECMWF), which operates on 983,040 CPU cores, and the U.K. Met Office\u2019s supercomputer, which uses more than 1.5 million CPU cores and consumes 2.7 megawatts of power.\n\nThe global push toward energy efficiency is urging a rethink of HPC system design. Accelerated computing, harnessing the power of GPUs, offers a promising, energy-efficient alternative that speeds up computations.\n\nNVIDIA GPUs have made a significant impact on globally adopted weather models, including those from ECMWF, the Max Planck Institute for Meteorology, the German Meteorological Service and the National Center for Atmospheric Research.\n\nGPUs enhance performance up to 24x, improve energy efficiency, and reduce costs and space requirements.\n\n\u201cTo make reliable weather predictions and climate projections a reality within power budget limits, we rely on algorithmic improvements and hardware where NVIDIA GPUs are an alternative to CPUs,\u201d said Oliver Fuhrer, head of numerical prediction at MeteoSwiss, the Swiss national office of meteorology and climatology.\n\nNVIDIA\u2019s AI-based weather-prediction model FourCastNet offers competitive accuracy with orders of magnitude greater speed and energy efficiency compared with traditional NWP methods. The latest version of FourCastNet, based on the Spherical Fourier Neural Operator , rapidly produces months-long forecasts and allows for the generation of large ensembles \u2014 or groups of simulations with slight variations in starting conditions \u2014 for high-confidence, extreme weather risk predictions weeks in advance.\n\nFor example, based on historical weather and climate data from ECMWF, FourCastNet ensembles accurately predicted increased risk of extreme temperatures during Africa\u2019s hottest recorded heatwave, in July 2018 .\""
  },
  {
    "question": "What is the name of the software-defined platform that Jaguar Land Rover will use for its next-generation cars?",
    "document": "SmFndWFyIExhbmQgUm92ZXIgMi8xNi8yMi5wZGY=.pdf",
    "ground_truth_answer": "The software-defined platform used by Jaguar Land Rover for its next-generation cars is called NVIDIA DRIVE.",
    "ground_truth_context": "\"\nFor more information, visit www.media.jaguarlandrover.com.\n\nCertain statements in this press release including, but not limited to, statements as to: the benefits, impact, and features of NVIDIA\u2019s products and technologies, including the NVIDIA DRIVE platform, DRIVE Hyperion, DRIVE Orin, NVIDIA DGX, DRIVE Sim, and NVIDIA Omniverse; the benefits and impact of NVIDIA\u2019s collaboration with Jaguar Land Rover; all new Jaguar and Land Rover vehicles being built on the NVIDIA DRIVE software-defined platform; next-generation cars transforming auto into one of the largest and most advanced technology industries; and fleets of software-defined, programmable cars being enhanced with new functionalities and services for the life of the vehicle are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing product and technologies; market acceptance of our products or our partners products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the companys website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward- looking statements to reflect future events or circumstances.\n\n\u00a9 2022 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, NVIDIA DRIVE, DRIVE Orin, NVIDIA DGX, NVIDIA DRIVE Hyperion and NVIDIA Omniverse are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability and specifications are subject to change without notice.\n\nMarie Labrie Automotive +1-408-921-6987 mlabrie@nvidia.com\""
  },
  {
    "question": "What was the name of the contest that Lavit won?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDgvMDkvaW4tdGhlLW52aWRpYS1zdHVkaW8tYXVndXN0LTkv.pdf",
    "ground_truth_answer": "#MadeInMachinima",
    "ground_truth_context": "\"\nPowered by a GeForce RTX 3090 GPU , Lavit\u2019s creative workflow showcases the breadth and interoperability of Omniverse, its Apps and Connectors . He used lighting and scene setting to establish the short film\u2019s changing mood, helping audiences understand the story\u2019s progression. Its introduction, for example, is bright and clear. The film then gets darker, conveying the idea of the unknown as the\n\ncharacter starts his journey.\n\nLavit storyboarded on paper before starting his digital process with the Machinima and Omniverse Create apps. He quickly turned to NVIDIA\u2019s built-in 3D asset library, filled with free content from Mount & Blade II: Bannerlord , Mechwarrior 5: Mercenaries , Squad and more \u2013 to populate the scene.\n\nThen, Lavit used Autodesk Maya to create 3D models for some of his hero assets \u2014 like the protagonist Sol\u2019s spaceship. The Maya Omniverse Connector allowed him to visualize scenes within Omniverse Create. He also benefited from RTX-accelerated ray tracing and AI denoising in Maya, resulting in highly interactive and photorealistic renders.\n\nNext, Lavit textured the models in Adobe Substance 3D, which also has an Omniverse Connector . Substance 3D uses NVIDIA Iray rendering, including for textures and substances. It also features RTX-accelerated light- and ambient-occlusion baking, which optimizes assets in seconds.\n\nLavit then returned to Machinima for final layout, animation and render. The result was composited using Adobe After Effects, with an extra layer of effects and music. What turned into the contest-winning piece of art ultimately was \u201ca pretty simple workflow to keep the complexity to a minimum,\u201d Lavit said.\n\nTo power his future creativity from anywhere, Lavit won an ASUS ProArt StudioBook 16. This NVIDIA Studio laptop packs top-of-the-line technology into a device that enables users to work on the go with world-class power from a GeForce RTX 3080 Ti Laptop GPU and beautiful 4K display.\n\nLavit, born in France and now based in the U.S., sees every project as an adventure. Living in a different country from where he was born changed his vision of art, he said. Lavit regularly finds inspiration from the French graphic novel series, The Incal , which is written by Alejandro Jodorowsky and illustrated by renowned cartoonist Jean Giraud, aka M\u0153bius.\n\nThe next generation of creative professionals is heading back to campus. Choosing the right NVIDIA Studio laptop can be tricky, but students can use this guide to find the perfect tool to power their creativity \u2014 like the Lenovo Slim 7i Pro X , an NVIDIA Studio laptop now available with a GeForce RTX 3050 Laptop GPU.\n\nWhile the #MadeInMachinima contest has wrapped, creators can graduate to an NVIDIA RTX A6000 GPU in the #ExtendOmniverse contest , running through Friday, Sept. 9, at 5 p.m. PT. Perform something akin to magic by making your own NVIDIA Omniverse Extension for a chance to win an RTX A6000 or GeForce RTX 3090 Ti GPU. Winners will be announced in September at GTC .\""
  },
  {
    "question": "Who is the CEO of NVIDIA?",
    "document": "VXBjb21pbmcgRXZlbnQgRmluYW5jaWFsIDIvMjIvMjIucGRm.pdf",
    "ground_truth_answer": "The CEO of NVIDIA is Jensen Huang.",
    "ground_truth_context": "\"\nNVIDIA Announces Upcoming Event for Financial Community\n\nSANTA CLARA, Calif., Feb. 22, 2022 -- NVIDIA will present at the following event for the financial community:\n\nMorgan Stanley Technology, Media & Telecom Conference Monday, March 7, at 10:55 a.m. Pacific Time\n\nInterested parties can listen to a live audio webcast of NVIDIA\u2019s presentation at this event, available at investor.nvidia.com. A replay of the webcast will be available for 90 days afterward.\n\nAbout NVIDIA NVIDIA\u2019s (NASDAQ: NVDA) invention of the GPU in 1999 sparked the growth of the PC gaming market and has redefined modern computer graphics, high performance computing and artificial intelligence. The company\u2019s pioneering work in accelerated computing and AI is reshaping trillion-dollar industries, such as transportation, healthcare and manufacturing, and fueling the growth of many others. More information at https://nvidianews.nvidia.com/.\n\n\u00a9 2022 NVIDIA Corporation. All rights reserved. NVIDIA and the NVIDIA logo are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability and specifications are subject to change without notice.\n\nSimona Jankowski Investor Relations sjankowski@nvidia.com Robert Sherbin Corporate Communications rsherbin@nvidia.com\""
  },
  {
    "question": "What is the name of the app created by Photomath that helps students and their parents brush up on everything from arithmetic to calculus?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDkvMDYvYWktc3RhcnR1cHMtZWR1Y2F0aW9uLw==.pdf",
    "ground_truth_answer": "Photomath",
    "ground_truth_context": "\"\nModel Teachers: Startups Make Schools Smarter With Machine Learning SimInsights and Photomath show some of the ways startups are enhancing education with NVIDIA AI.\n\nAuthor: Rick Merritt\n\nLike two valedictorians, SimInsights and Photomath tell stories worth hearing about how AI is advancing education.\n\nSimInsights in Irvine, Calif., uses NVIDIA conversational AI to make virtual and augmented reality classes lifelike for college students and employee training.\n\nPhotomath \u2014 founded in Zagreb, Croatia and based in San Mateo, Calif. \u2014 created an app using computer vision and natural language processing to help students and their parents brush up on everything from arithmetic to calculus.\n\nBoth companies are a part of NVIDIA Inception , a free, global program that nurtures cutting-edge startups.\n\nRajesh Jha loved simulations since he developed a physics simulation engine for mechanical parts in college, more than 25 years ago. \u201cSo, I put sim in the name when I started my own company in 2009,\u201d he said.\n\nSimInsights originally developed web and mobile training simulations. When AR and VR platforms became available, Jha secured a grant to develop HyperSkill. Now the company\u2019s main product, it\u2019s a cloud-based, AI-powered 3D simulation authoring and analytics tool that makes training immersive.\n\nThe software helped UCLA\u2019s medical center build a virtual clinic to train students. But they complained about the low accuracy of its rules-based conversational AI, so Jha took data from the first class and trained a deep neural network using NVIDIA Riva , GPU-accelerated software for building speech AI applications.\n\n\u201cThere was a quick uptick in the quality, and they say it\u2019s the most realistic training they\u2019ve used,\u201d said Jha.\n\nNow, UCLA wants to apply the technology to train thousands of nurses on dealing with infectious diseases.\n\n\u201cThere\u2019s a huge role for conversational AI in education and training because it personalizes the experience,\u201d he said. \u201cAnd a lot of research shows if you can do that, people learn more and retain it longer.\u201d\n\nBecause SimInsights is an NVIDIA Inception member, it got early access to Riva and NVIDIA TAO , a toolkit that accelerates evaluating and training AI models with transfer learning. They\u2019ve become standard parts of the company\u2019s workflow.\n\nAs for Riva, \u201cit\u2019s a powerful piece of software, and our team really appreciates working with NVIDIA to brainstorm our next steps,\u201d Jha said.\n\nSpecifically, SimInsights aims to develop larger conversational AI models with more functions, such as question answering so students can point to objects in a scene and ask about them.\n\n\u201cAs Riva gives us more capabilities, we\u2019ll incorporate them into HyperSkill to make digital learning as good as working with an expert \u2014 it will take a while, but this is the way to get there,\u201d he said.\""
  },
  {
    "question": "What is the goal of the Alliance for OpenUSD?",
    "document": "T3BlblVTRCBBbGxpYW5jZSA4LzEvMjMucGRm.pdf",
    "ground_truth_answer": "The goal of the Alliance for OpenUSD is to accelerate the adoption and development of OpenUSD as a broadly adopted standard for 3D interoperability, and to promote its use across various industries and applications.",
    "ground_truth_context": "\"\n\u201cAt Adobe, we believe in providing artists a set of flexible and powerful solutions running on a variety of devices,\u201d said Guido Quaroni, Senior Director of Engineering, 3D&I at Adobe. \u201cLeveraging a common 3D data representation during the creative process multiplies the value brought by each package and device. OpenUSD was created to be one of these \u2018multipliers\u2019 and we are excited to see a diverse group of companies joining together to support this innovative and open technology.\u201d\n\n\u201cOpenUSD will help accelerate the next generation of AR experiences, from artistic creation to content delivery, and produce an ever-widening array of spatial computing applications,\u201d said Mike Rockwell, Apple\u2019s vice president of the Vision Products Group. \u201cApple has been an active contributor to the development of USD, and it is an essential technology for the groundbreaking visionOS platform, as well as the new Reality Composer Pro developer tool. We look forward to fostering its growth into a broadly adopted standard.\u201d\n\n\u201cWhether you\u2019re building CG worlds or digital twins or looking ahead to the 3D web, content creators need a cohesive way to collaborate and share data across tools, services, and platforms,\u201d said Gordon Bradley, Fellow, Media & Entertainment, Autodesk. \u201cAutodesk is excited to support the Alliance for OpenUSD as it drives 3D interoperability for visual effects, animation, and beyond, and supports our vision to help customers design and make a better world.\u201d\n\n\u201cOpenUSD gives 3D developers, artists, and designers the complete foundation to tackle large-scale industrial, digital content creation, and simulation workloads with broad multi-app interoperability,\u201d said Guy Martin, Director of Open Source and Standards at NVIDIA. \u201cThis alliance is a unique opportunity to accelerate OpenUSD collaboration globally by building formal standards across industries and initiatives to realize 3D worlds and industrial digitalization.\u201d\n\nAOUSD steering committee members will be speaking at both the Academy Software Foundation\u2019s Open Source Days on Aug. 6 and at the SIGGRAPH conference at the Autodesk Vision Series on Aug. 8 at 1 p.m. PT in Room 404A.\n\nTo learn more about AOUSD and how to get involved, visit www.aousd.org. To tune into the Academy Software Foundation panel on USD on Aug. 6, 2023, visit the website.\n\nAbout the Joint Development Foundation The Joint Development Foundation (JDF), part of the Linux Foundation Family, provides the corporate and legal infrastructure to enable organizations to develop technical specifications, standards, data sets, and source code. JDF projects such as Ultra Ethernet Consortium, Alliance for Open Media, Coalition for Content Provenance and Authenticity, and Overture Maps Foundation innovate markets, lead change, and champion open participation and licensing policies. For more information, please visit us at jointdevelopment.org.\""
  },
  {
    "question": "What is the purpose of the NVIDIA BioNeMo LLM Service?",
    "document": "TmVNbyBMTE0gU2VydmljZSA5LzIwLzIyLnBkZg==.pdf",
    "ground_truth_answer": "The BioNeMo LLM Service enables researchers to discover patterns and insights in biological sequences, including protein, DNA, and biochemical data.",
    "ground_truth_context": "\"\nNVIDIA Launches Large Language Model Cloud Services to Advance AI and Digital Biology\n\nNVIDIA NeMo LLM Service Helps Developers Customize Massive Language Models; NVIDIA BioNeMo Service Helps Researchers Generate and Predict Molecules, Proteins, DNA\n\nGTC\u2014NVIDIA today announced two new large language model cloud AI services \u2014 the NVIDIA NeMo Large Language Model Service and the NVIDIA BioNeMo LLM Service \u2014 that enable developers to easily adapt LLMs and deploy customized AI applications for content generation, text summarization, chatbots, code development, as well as protein structure and biomolecular property predictions, and more.\n\nThe NeMo LLM Service allows developers to rapidly tailor a number of pretrained foundation models using a training method called prompt learning on NVIDIA-managed infrastructure. The NVIDIA BioNeMo Service is a cloud application programming interface (API) that expands LLM use cases beyond language and into scientific applications to accelerate drug discovery for pharma and biotech companies.\n\n\u201cLarge language models hold the potential to transform every industry,\u201d said Jensen Huang, founder and CEO of NVIDIA. \u201cThe ability to tune foundation models puts the power of LLMs within reach of millions of developers who can now create language services and power scientific discoveries without needing to build a massive model from scratch.\u201d\n\nNeMo LLM Service Boosts Accuracy With Prompt Learning, Accelerates Deployments With the NeMo LLM Service, developers can use their own training data to customize foundation models ranging from 3 billion parameters up to Megatron 530B, one of the world\u2019s largest LLMs. The process takes just minutes to hours compared with the weeks or months required to train a model from scratch.\n\nModels are customized with prompt learning, which uses a technique called p-tuning. This allows developers to use just a few hundred examples to rapidly tailor foundation models that were originally trained with billions of data points. The customization process generates task-specific prompt tokens, which are then combined with the foundation models to deliver higher accuracy and more relevant responses for specific use cases.\n\nDevelopers can customize for multiple use cases using the same model and generate many different prompt tokens. A playground feature provides a no-code option to easily experiment and interact with models, further boosting the effectiveness and accessibility of LLMs for industry-specific use cases.\n\nOnce ready to deploy, the tuned models can run on cloud instances, on-premises systems or through an API.\n\nBioNeMo LLM Service Enables Researchers to Tap Power of Massive Models The BioNeMo LLM Service includes two new BioNeMo language models for chemistry and biology applications. It provides support for protein, DNA and biochemical data to help researchers discover patterns and insights in biological sequences.\""
  },
  {
    "question": "What was the speedup achieved by the IRS using the RAPIDS Accelerator for data engineering and data science workflows?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDgvMjgvc3BhcmstcmFwaWRzLWVuZXJneS1lZmZpY2llbmN5Lw==.pdf",
    "ground_truth_answer": "The IRS achieved a 20x speedup in data engineering and data science workflows using the RAPIDS Accelerator.",
    "ground_truth_context": "\"\nAdobe used accelerated computing on its Intelligent Services platform, which helps marketing teams speed analytics with AI.\n\nIt found that, using the RAPIDS Accelerator, a single NVIDIA GPU node could outperform a 16-node CPU cluster by 33% while slashing computing costs by 70%.\n\nIn a separate test, GPU-accelerated RAPIDS libraries trained an AI model 7x faster, saving 90% of the cost of running the same job on CPUs.\n\n\u201cThis is an amazing cost savings and speed-up,\u201d said Lei Zhang, a machine learning engineer at Adobe in a talk at GTC ( free with registration ).\n\nCPUs weren\u2019t powerful enough to ingest the 3+ terabyte dataset it needed to analyze, so the IRS turned to the RAPIDS Accelerator.\n\nA Spark cluster of GPU-powered servers processed the load and opened the door to tackling even bigger datasets.\n\n\u201cWe\u2019re currently implementing this integration and already seeing over 20x speed improvements at half the cost for our data engineering and data science workflows,\u201d said Joe Ansaldi, technical branch chief of the research and applied analytics and statistics division at the IRS, in a blog .\n\nPerformance speedups and cost savings vary across workloads. That\u2019s why NVIDIA offers an accelerated Spark analysis tool .\n\nThe tool shows users what the RAPIDS Accelerator can deliver on their applications without any code changes. It also helps users tune GPU acceleration to get the best results on their workloads.\n\nOnce the RAPIDS Accelerator is boosting the bottom line, companies can calculate their energy savings and report their progress in protecting the planet.\n\nLearn more in this solution brief . And watch the video below to see how the Cloudera Data Platform delivered a 44x speedup with the RAPIDS Accelerator for Apache Spark.\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/08/28/spark-rapids-energy-efficiency/\""
  },
  {
    "question": "How has EMVision benefited from being a member of NVIDIA Inception?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTIvMDUvZW12aXNpb24tcG9ydGFibGUtYnJhaW4tc2Nhbm5lci8=.pdf",
    "ground_truth_answer": "EMVision has shortened product development cycles and go-to-market time as a member of NVIDIA Inception.",
    "ground_truth_context": "\"\nEMVision uses NVIDIA DGX for hardware verification and optimization, as well as for prototyping and training AI models. EMVision has trained its AI models 10x faster using NVIDIA DGX compared with other systems, according to Weinberger.\n\nEach brain scanner has an NVIDIA Jetson AGX Xavier module on board for energy-efficient AI inference at the edge. And the startup is looking to use NVIDIA Jetson Orin Nano modules for\n\nnext-generation edge AI.\n\n\u201cThe interactions between low-energy electromagnetic signals and brain tissue are incredibly complex,\u201d Weinberger said. \u201cMaking sense of these signal interactions to identify if pathologies are present and recreate quality images wouldn\u2019t be possible without the massive power of NVIDIA GPU-accelerated computing.\u201d\n\nAs a member of NVIDIA Inception, a free, global program for cutting-edge startups, EMVision has shortened product development cycles and go-to-market time, Weinberger added.\n\nSubscribe to NVIDIA healthcare news and learn more about NVIDIA Inception .\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/12/05/emvision-portable-brain-scanner/\""
  },
  {
    "question": "What is the name of the platform that enables real-time 3D design collaboration and virtual world simulation for creators?",
    "document": "TmV3IEdlRm9yY2UgTGFwdG9wcyBhbmQgRGVza3RvcHMgMS80LzIyLnBkZg==.pdf",
    "ground_truth_answer": "The platform that enables real-time 3D design collaboration and virtual world simulation for creators is called NVIDIA Omniverse.",
    "ground_truth_context": "\"\nThis includes a major update to NVIDIA Canvas, a painting application that uses AI to generate landscape images from simple brush strokes. Built from NVIDIA\u2019s GauGAN2\u00ae research, the app produces images that are 4x higher resolution than in the past, with five additional elements like flowers and bushes. The new Canvas app is free to download.\n\nThe Studio platform also includes a wide range of NVIDIA Studio laptops, with designs from ASUS, MSI and Razer powered by the new GeForce RTX 3080 Ti and 3070 Ti laptop GPUs. With the latest RTX GPUs, these laptops are on average 7x faster for 3D rendering than the latest MacBook Pro 16.(1) They support more than 200 creative applications, as well as RTX- accelerated ray tracing, AI and NVIDIA\u2019s high-performance video processor, making them the perfect tool for any creator workflow.\n\nNVIDIA Omniverse Launches For Creators Further enriching the NVIDIA Studio ecosystem, NVIDIA Omniverse is now available at no cost to millions of individual creators with GeForce RTX and NVIDIA RTX GPUs. NVIDIA\u2019s real-time 3D design collaboration and virtual world simulation platform empowers artists, designers and creators to connect and collaborate in leading design applications from their RTX- powered laptop or workstation.\n\nA new platform feature, Omniverse Nucleus Cloud, is enabling simple \u201cone-click-to-collaborate\u201d sharing of large Omniverse 3D scenes. Artists can collaborate in real time from across the room or the globe without transferring massive datasets.\n\nNVIDIA also introduced new platform developments for Omniverse Machinima \u2014 the Omniverse app that enables real-time collaboration to animate and manipulate characters in virtual worlds \u2014 with additional free game characters, objects and environments. Omniverse Audio2Face, which quickly and easily generates expressive facial animation from just an audio source, has been updated with blendshape support and direct export to Epic\u2019s MetaHuman.\n\nIntroducing the New GeForce RTX 3050 NVIDIA further expanded its family of NVIDIA Ampere architecture-based GPUs with the GeForce RTX 3050.\n\nBringing the performance and efficiency of the architecture to more gamers than ever, the RTX 3050 is the first 50-class desktop GPU to power the latest ray-traced games at over 60 frames per second. RTX 3050 makes ray tracing, which is the new standard in gaming, more accessible than ever before.\n\nWith 75 percent of gamers still playing on GTX GPUs, the 3050, which also includes second-generation RT cores as well as third generation Tensor cores for DLSS and AI, represents a compelling upgrade opportunity to step up to RTX.\n\nThe RTX 3050, which comes with 8GB of GDDR6 memory, starts at just $249 and will be available on Jan. 27 from NVIDIA\u2019s worldwide partners.\""
  },
  {
    "question": "What is the name of the AI brain of the car that Jaguar Land Rover will use in its vehicles?",
    "document": "SmFndWFyIExhbmQgUm92ZXIgMi8xNi8yMi5wZGY=.pdf",
    "ground_truth_answer": "DRIVE Orin\u2122 centralised AV computers",
    "ground_truth_context": "\"\nJaguar Land Rover Announces Partnership With NVIDIA\n\nAs part of Jaguar Land Rover\u2019s Reimagine strategy, partnership will transform the modern luxury experience for customers starting in 2025 Software experts from both companies will jointly develop AI-powered autonomous driving and connected services for all future vehicles built on NVIDIA DRIVE Next-generation safety and unique, brand-focused digital services enabled by NVIDIA AI\n\nJaguar Land Rover has formed a multi-year strategic partnership with NVIDIA, the leader in artificial intelligence (AI) and computing, to jointly develop and deliver next-generation automated driving systems plus AI-enabled services and experiences for its customers.\n\nStarting in 2025, all new Jaguar and Land Rover vehicles will be built on the NVIDIA DRIVE\u2122 software-defined platform \u2014 delivering a wide spectrum of active safety, automated driving and parking systems as well as driver assistance systems. Inside the vehicle, the system will deliver AI features, including driver and occupant monitoring, as well as advanced visualisation of the vehicle\u2019s environment.\n\nThis full-stack solution is based on NVIDIA DRIVE Hyperion\u2122, which features DRIVE Orin\u2122 centralised AV computers; DRIVE AV and DRIVE IX software; safety, security and networking systems; plus, surround sensors. DRIVE Orin is the AI brain of the car and runs the Jaguar Land Rover Operating System, while DRIVE Hyperion is the central nervous system.\n\nJaguar Land Rover will also leverage in-house developed data centre solutions with NVIDIA DGX\u2122 for training AI models and DRIVE Sim software built on NVIDIA Omniverse\u2122 for real-time physically accurate simulation. Jaguar Land Rover\u2019s software-defined features and its end-to-end verification and validation architecture will enable the delivery of innovative assisted and automated driving services throughout the life of the vehicle via over-the-air software updates.\n\nThierry Bollor\u00e9, Jaguar Land Rover Chief Executive Officer, said: \u201cCollaboration and knowledge-sharing with industry leader NVIDIA is essential to realising our Reimagine strategy, setting new benchmarks in quality, technology and sustainability.\n\n\u201cJaguar Land Rover will become the creator of the world\u2019s most desirable luxury vehicles and services for the most discerning customers. Our long-term strategic partnership with NVIDIA will unlock a world of potential for our future vehicles as the business continues its transformation into a truly global, digital powerhouse.\u201d\n\nJensen Huang, NVIDIA founder and Chief Executive Officer, said: \u201cNext-generation cars will transform automotive into one of the largest and most advanced technology industries. Fleets of software-defined, programmable cars will offer new functionalities and services for the life of the vehicles. We are thrilled to partner with Jaguar Land Rover to reimagine the future of transportation and create the most advanced cars.\u201d\""
  },
  {
    "question": "What is the purpose of Pegatron's digital twins of inspection machines?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDgvMTYvcGVnYXRyb24tYWktb21uaXZlcnNlLw==.pdf",
    "ground_truth_answer": "The digital twins of inspection machines allow remote workers to manage them remotely, provide better insight into predictive maintenance, and simulate software updates before deploying them to a physical machine.",
    "ground_truth_context": "\"\nAs part of its AI inference work, the system analyzes more than 10 million images a day using NVIDIA A40 and other GPUs.\n\nPegatron uses NVIDIA Triton Inference Server , open-source software that helps deploy, run and scale AI models across all types of processors, and frameworks. It works hand-in-hand with NVIDIA\n\nTensorRT , software that simplifies neural networks to reduce latency.\n\n\u201cTriton and TensorRT make it easy to serve multiple clients and convert jobs to the most cost-effective precision levels,\u201d he said.\n\nHsiao\u2019s team optimizes pretrained AI models it downloads in integrated Kubernetes containers from the NVIDIA NGC hub for GPU-optimized software.\n\n\u201cNGC is very helpful because we get with one click the deep learning frameworks and all the other software components we need, stuff that used to take us a lot of time to pull together,\u201d he said.\n\nTaking another step in smarter manufacturing, Pegatron is piloting NVIDIA Omniverse , a platform for developing digital twins\n\nIt has two use cases so far. First, testing Omniverse Replicator to generate synthetic data of what products coming down the inspection line might look like under different lighting conditions or orientations. This information will make its perception models smarter.\n\nSecond, it\u2019s creating digital twins of inspection machines. That lets remote workers manage them remotely, have better insight into predictive maintenance and simulate software updates before deploying them to a physical machine.\n\n\u201cToday, when a system goes down, we can only check logs that might be incomplete, but with Omniverse, we can replay what happened to understand how to fix it, or, run simulations to predict how it will behave in the future,\u201d he said.\n\nWhat\u2019s more, industrial engineers who care about throughput, automation engineers responsible for downtime, and equipment engineers who handle maintenance can work together on the same virtual system at the same time, even when logging in from different countries.\n\nIf all goes well, Pegatron could have Omniverse available on its inspection machines before the end of the year.\n\nMeanwhile, Hsiao is looking for partners who can help build virtual versions of a whole production line in Omniverse. Longer term, his vision is to create a digital twin of an entire factory.\n\n\u201cIn my opinion, the greatest impact will come from building a full virtual factory so we can try out things like new ways to route products through the plant,\u201d he said. \u201cWhen you just build it out without a simulation first, your mistakes are very costly.\u201d\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/08/16/pegatron-ai-omniverse/\""
  },
  {
    "question": "What is the focus of the blog post discussed in the AI Podcast?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDQvMjYvaW50ZWxsaWdlbnQtdmVoaWNsZS1pbnRlcmlvcnMv.pdf",
    "ground_truth_answer": "The focus of the blog post is on intelligent vehicle interiors and how AI is transforming the driving experience.",
    "ground_truth_context": "\"\nMake the AI Podcast better: Have a few minutes to spare? Fill out this listener survey .\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/04/26/intelligent-vehicle-interiors/\""
  },
  {
    "question": "How did Sierra Division decide on the mood of the story they wanted to tell with their in-progress assets?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDcvMTEvc2llcnJhLWRpdmlzaW9uLW9tbml2ZXJzZS1vcGVudXNkLWNvbXBvc2VyLw==.pdf",
    "ground_truth_answer": "Sierra Division analyzed daytime, nighttime, rainy, and cloudy scenarios to see how the scene resonated emotionally, helping them decide on a cloudy environment with well-placed lights to evoke feelings of mystery and intrigue.",
    "ground_truth_context": "\"\n\u201cSince everything is shared in OpenUSD, our asset library is easily accessible and reduces the time needed to access materials and make edits on the fly,\u201d Norris added. \u201cThis helps spur inspirational and\n\nimaginational forces.\u201d\n\nDuring the review phase, the team can compare photorealistic models with incredible visual fidelity side by side in a shared space, ensuring the models are \u201ccreated to the highest set of standards,\u201d said Norris.\n\nSierra Division\u2019s The Oil Rig video is set on Earth\u2019s last operational fossil fuel rig, which is visited by a playful drone named Quark. The piece\u2019s storytelling takes the audience through an impeccably detailed environment.\n\nA scene as complex as the one above required blockouts in Unreal Engine. The team snapped models together from a set of greybox modular pieces, ensuring the environment bits were easy to work with. Once satisfied with the environment concept and layout, the team added further detail to the models.\n\nNorris\u2019 Lenovo ThinkPad P73 NVIDIA Studio laptop with NVIDIA RTX A5000 graphics powered NVIDIA DLSS technology to increase the interactivity of the viewport \u2014 by using AI to upscale frames rendered at lower resolution while retaining high-fidelity detail.\n\nSierra Division then created tiling textures, trim sheets and materials to apply to near-finalized models. The studio used Adobe Substance 3D Painter to design custom textures with edge wear and grunge, taking advantage of RTX-accelerated light and ambient occlusion for baking and optimizing assets in seconds.\n\nNext, lighting scenarios were tested in the Omniverse USD Composer app with the Unreal Engine Connector , which eliminates the need to upload, download and refile formats, thanks to OpenUSD.\n\n\u201cWith OpenUSD, it\u2019s very easy to open the same file you\u2019re viewing in the engine and quickly make edits without having to re-import,\u201d said Norris.\n\nSierra Division analyzed daytime, nighttime, rainy and cloudy scenarios to see how the scene resonated emotionally, helping to decide the mood of the story they wanted to tell with their in-progress assets. They settled on a cloudy environment with well-placed lights to evoke feelings of mystery and intrigue.\n\n\u201cFrom story-building to asset and scene creation to final renders with RTX, AI and GPU-accelerated features helped us every step of the way.\u201d \u2014 Jacob Norris\n\nFrom here, the team added cameras to the scene to determine compositions for final renders.\n\n\u201cIf we were to try to compose the entire environment without cameras or direction, it would take much longer, and we wouldn\u2019t have perfectly laid-out camera shots nor specifically lit renders,\u201d said Norris. \u201cIt\u2019s just much easier and more fun to do it this way and to pick camera shots earlier on.\u201d\n\nFinal renders were exported lightning fast with Norris\u2019 RTX A5000 GPU into Adobe Photoshop. Over 30 GPU-accelerated features gave Norris plenty of options to play with colors and contrast, and make final image adjustments smoothly and quickly.\""
  },
  {
    "question": "Which company provides an AI-powered identity-verification solution for fraud prevention and compliance?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTAvMTEvbnZpZGlhLWF0LW1vbmV5MjAyMC8=.pdf",
    "ground_truth_answer": "Veriff",
    "ground_truth_context": "\"\nAuditoria \u2014 Provides an AI-driven software-as-a-service for corporate finance that automates finance processes in vendor management, accounts payable and receivable, and accruals to accelerate cash performance using natural language processing, AI and machine learning.\n\nClarity AI \u2014 Offers a sustainability technology platform that uses machine learning to deliver environmental and social insights to investors, consumers, companies and governments. The customizable, scalable sustainability tech kit can be built into existing workflows \u2014 for investors, companies and governments \u2014 and existing purchasing patterns for consumers. This additional relevant information helps anyone, anywhere to efficiently and confidently assess, analyze and report valuable information on anything related to sustainability.\n\nStori Card \u2014 Offers a mobile-first platform that expands access to credit cards for underserved populations. It gives every customer a chance to obtain a credit card and build their credit history without complicated paperwork, a credit history or annual fees.\n\nVeriff \u2014 Provides an AI-powered identity-verification solution for fraud prevention, know-your-customer compliance, and fast conversions of valuable customers.\n\nNVIDIA and Deloitte are bringing new services based on the NVIDIA AI and Omniverse platforms to help enterprises worldwide build and operate state-of-the-art AI and metaverse services, including internet-of-things edge AI, speech AI, recommenders, customer service chatbots, cybersecurity, digital twins and more.\n\nDeloitte will present at Money20/20 and showcase demos at booth 10 in the innovation zone on the expo floor.\n\nTo schedule a meeting with an NVIDIA AI expert, visit the company\u2019s meeting space on the show floor or create a request via the Money20/20 mobile app, which can be accessed following conference registration .\n\nLearn more about NVIDIA and AWS at Money20/20 .\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/10/11/nvidia-at-money2020/\""
  },
  {
    "question": "What is a foundation model in AI?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTAvMTAvbGxtcy1haS1ob3Jpem9uLw==.pdf",
    "ground_truth_answer": "A foundation model in AI is a type of large language model (LLM) that has only recently begun to transform the way AI systems are built and deployed in the world, according to a July paper by the Stanford center.",
    "ground_truth_context": "\"\nIt\u2019s another example of what the Stanford center in a July paper called a paradigm shift in AI. \u201cFoundation models have only just begun to transform the way AI systems are built and deployed in the world,\u201d it said.\n\nLearn how companies around the world are implementing LLMs with NVIDIA Triton for many use cases.\n\nOriginal URL: https://blogs.nvidia.com/blog/2022/10/10/llms-ai-horizon/\""
  },
  {
    "question": "How much more bandwidth does NVLink-C2C have compared to PCIe Gen 5?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDkvMjAvZ3JhY2UtaG9wcGVyLXJlY29tbWVuZGVyLXN5c3RlbXMv.pdf",
    "ground_truth_answer": "NVLink-C2C has 7x the bandwidth of PCIe Gen 5, carrying data at 900 gigabytes per second.",
    "ground_truth_context": "\"\nWhy the New NVIDIA Grace Hopper Superchip Is Ideal for Next-Gen Recommender Systems\n\nPerformance of the massive AI models that help users personalize the internet will hit new levels of accuracy with the Grace Hopper Superchip.\n\nAuthor: Paresh Kharya\n\nRecommender systems, the economic engines of the internet, are getting a new turbocharger: the NVIDIA Grace Hopper Superchip .\n\nEvery day, recommenders serve up trillions of search results, ads, products, music and news stories to billions of people. They\u2019re among the most important AI models of our time because they\u2019re incredibly effective at finding in the internet\u2019s pandemonium the pearls users want.\n\nThese machine learning pipelines run on data, terabytes of it. The more data recommenders consume, the more accurate their results and the more return on investment they deliver.\n\nTo process this data tsunami, companies are already adopting accelerated computing to personalize services for their customers. Grace Hopper will take their advances to the next level.\n\nPinterest, the image-sharing social media company, was able to move to 100x larger recommender models by adopting NVIDIA GPUs. That increased engagement by 16% for its more than 400 million users.\n\n\u201cNormally, we would be happy with a 2% increase, and 16% is just a beginning,\u201d a software engineer at the company said in a recent blog . \u201cWe see additional gains \u2014 it opens a lot of doors for opportunities.\u201d\n\nThe next generation of the NVIDIA AI platform promises even greater gains for companies processing massive datasets with super-sized recommender models.\n\nBecause data is the fuel of AI, Grace Hopper is designed to pump more data through recommender systems than any other processor on the planet.\n\nGrace Hopper achieves this because it\u2019s a superchip \u2014 two chips in one unit, sharing a superfast chip-to-chip interconnect. It\u2019s an Arm-based NVIDIA Grace CPU and a Hopper GPU that communicate over NVIDIA NVLink-C2C .\n\nWhat\u2019s more, NVLink also connects many superchips into a super system, a computing cluster built to run terabyte-class recommender systems.\n\nNVLink carries data at a whopping 900 gigabytes per second \u2014 7x the bandwidth of PCIe Gen 5, the interconnect most leading edge upcoming systems will use.\n\nThat means Grace Hopper feeds recommenders 7x more of the embeddings \u2014 data tables packed with context \u2014 that they need to personalize results for users.\n\nThe Grace CPU uses LPDDR5X, a type of memory that strikes the optimal balance of bandwidth, energy efficiency, capacity and cost for recommender systems and other demanding workloads. It provides 50% more bandwidth while using an eighth of the power per gigabyte of traditional DDR5 memory subsystems.\n\nAny Hopper GPU in a cluster can access Grace\u2019s memory over NVLink. It\u2019s a feature of Grace Hopper that provides the largest pools of GPU memory ever.\n\nIn addition, NVLink-C2C requires just 1.3 picojoules per bit transferred, giving it more than 5x the energy efficiency of PCIe Gen 5.\""
  },
  {
    "question": "What are some potential uses of GET3D?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDkvMjMvM2QtZ2VuZXJhdGl2ZS1haS1yZXNlYXJjaC12aXJ0dWFsLXdvcmxkcy8=.pdf",
    "ground_truth_answer": "GET3D could be used to populate virtual worlds with diverse 3D objects, such as buildings, vehicles, and characters, for industries including gaming, robotics, architecture, and social media.",
    "ground_truth_context": "\"\nWorld-Class: NVIDIA Research Builds AI Model to Populate Virtual Worlds With 3D Objects, Characters\n\nAuthor: Isha Salian\n\nThe massive virtual worlds created by growing numbers of companies and creators could be more easily populated with a diverse array of 3D buildings, vehicles, characters and more \u2014 thanks to a new AI model from NVIDIA Research .\n\nTrained using only 2D images, NVIDIA GET3D generates 3D shapes with high-fidelity textures and complex geometric details. These 3D objects are created in the same format used by popular graphics software applications, allowing users to immediately import their shapes into 3D renderers and game engines for further editing.\n\nThe generated objects could be used in 3D representations of buildings, outdoor spaces or entire cities, designed for industries including gaming, robotics, architecture and social media.\n\nGET3D can generate a virtually unlimited number of 3D shapes based on the data it\u2019s trained on. Like an artist who turns a lump of clay into a detailed sculpture, the model transforms numbers into complex 3D shapes.\n\nWith a training dataset of 2D car images, for example, it creates a collection of sedans, trucks, race cars and vans. When trained on animal images, it comes up with creatures such as foxes, rhinos, horses and bears. Given chairs, the model generates assorted swivel chairs, dining chairs and cozy recliners.\n\n\u201cGET3D brings us a step closer to democratizing AI-powered 3D content creation,\u201d said Sanja Fidler, vice president of AI research at NVIDIA, who leads the Toronto-based AI lab that created the tool. \u201cIts ability to instantly generate textured 3D shapes could be a game-changer for developers, helping them rapidly populate virtual worlds with varied and interesting objects.\u201d\n\nGET3D is one of more than 20 NVIDIA-authored papers and workshops accepted to the NeurIPS AI conference, taking place in New Orleans and virtually, Nov. 26-Dec. 4.\n\nThe real world is full of variety: streets are lined with unique buildings, with different vehicles whizzing by and diverse crowds passing through. Manually modeling a 3D virtual world that reflects this is incredibly time consuming, making it difficult to fill out a detailed digital environment.\n\nThough quicker than manual methods, prior 3D generative AI models were limited in the level of detail they could produce. Even recent inverse rendering methods can only generate 3D objects based on 2D images taken from various angles, requiring developers to build one 3D shape at a time.\n\nGET3D can instead churn out some 20 shapes a second when running inference on a single NVIDIA GPU \u2014 working like a generative adversarial network for 2D images, while generating 3D objects. The larger, more diverse the training dataset it\u2019s learned from, the more varied and detailed the output.\""
  },
  {
    "question": "What are the two key barriers to widespread adoption of large language models identified by MosaicML?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDcvMTIvbW9zYWljbWwv.pdf",
    "ground_truth_answer": "The difficulty of coordinating a large number of GPUs to train a model and the costs associated with this process.",
    "ground_truth_context": "\"\nMosaicML Helps AI Users Boost Accuracy, Cut Costs and Save Time\n\nAuthor: Brian Caulfield\n\nStartup MosaicML is on a mission to help the AI community improve prediction accuracy, decrease costs and save time by providing tools for easy training and deployment of large AI models.\n\nIn this episode of NVIDIA\u2019s AI Podcast , host Noah Kravitz speaks with MosaicML CEO and co-founder Naveen Rao about how the company aims to democratize access to large language models .\n\nMosaicML, a member of NVIDIA\u2019s Inception program , has identified two key barriers to widespread adoption: the difficulty of coordinating a large number of GPUs to train a model and the costs associated with this process.\n\nMosaicML was in the news earlier this month when Databricks announced an agreement to acquire MosaicML for $1.3 billion.\n\nMaking training of models accessible is key for many companies that need control over model behavior, respect data privacy and iterate fast to develop new products based on AI.\n\nJules Anh Tuan Nguyen Explains How AI Lets Amputee Control Prosthetic Hand, Video Games\n\nA postdoctoral researcher at the University of Minnesota discusses his efforts to allow amputees to control their prosthetic limb \u2014 right down to the finger motions \u2014 with their minds.\n\nOverjet\u2019s Ai Wardah Inam on Bringing AI to Dentistry\n\nOverjet, a member of NVIDIA Inception, is moving fast to bring AI to dentists\u2019 offices. Dr. Wardah Inam, CEO of the company, discusses using AI to improve patient care.\n\nImmunai CTO and Co-Founder Luis Voloch on Using Deep Learning to Develop New Drugs\n\nLuis Voloch, co-founder and chief technology officer of Immunai, talks about tackling the challenges of the immune system with a machine learning and data science mindset.\n\nThe AI Podcast is now available through Amazon Music . Additionally, you can also get the AI Podcast through iTunes , Google Podcasts , Google Play , Castbox , DoggCatcher, Overcast , PlayerFM , Pocket Casts, Podbay , PodBean , PodCruncher, PodKicker, Soundcloud , Spotify , Stitcher and TuneIn .\n\nMake the AI Podcast better. Have a few minutes to spare? Fill out this listener survey .\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/07/12/mosaicml/\""
  },
  {
    "question": "What is the purpose of connecting Siemens Xcelerator and NVIDIA Omniverse?",
    "document": "U2llbWVucyBOVklESUEgNi8yOS8yMi5wZGY=.pdf",
    "ground_truth_answer": "The purpose of connecting Siemens Xcelerator and NVIDIA Omniverse is to enable an industrial metaverse with physics-based digital models from Siemens and real-time AI from NVIDIA, which will allow companies to make decisions faster and with increased confidence.",
    "ground_truth_context": "\"\nSiemens and NVIDIA to Enable Industrial Metaverse\n\nPartnership to transform the manufacturing industry with immersive experiences across the lifecycle from design through operation Companies will connect NVIDIA Omniverse and Siemens Xcelerator platforms to enable full-fidelity digital twins and connect software-defined AI systems from edge to cloud\n\nSiemens, a leader in industrial automation and software, infrastructure, building technology and transportation, and NVIDIA, a pioneer in accelerated graphics and artificial intelligence (AI), today announced an expansion of their partnership to enable the industrial metaverse and increase use of AI-driven digital twin technology that will help bring industrial automation to a new level. As a first step in this collaboration, the companies plan to connect Siemens Xcelerator, the open digital business platform, and NVIDIA Omniverse\u2122, a platform for 3D design and collaboration. This will enable an industrial metaverse with physics-based digital models from Siemens and real-time AI from NVIDIA in which companies make decisions faster and with increased confidence.\n\nThe addition of Omniverse to the open Siemens Xcelerator partner ecosystem will accelerate the use of digital twins that can deliver productivity and process improvements across the production and product lifecycles. Companies of all sizes will be able to employ digital twins with real-time performance data; create innovative industrial IoT solutions; leverage actionable insights from analytics at the edge or in the cloud; and tackle the engineering challenges of tomorrow by making visually rich, immersive simulations more accessible.\n\n\u201cPhotorealistic, physics-based digital twins embedded in the industrial metaverse offer enormous potential to transform our economies and industries by providing a virtual world where people can interact and collaborate to solve real-world problems. Through this partnership, we will make the industrial metaverse a reality for companies of all sizes,\u201d said Roland Busch, President and Chief Executive Officer, Siemens AG. \u201cFor over a decade, our digital twin technology has been helping customers across all industries to boost their productivity and today offer the industry\u2019s most comprehensive digital twin. When Siemens Xcelerator is connected to Omniverse, we will enable a real-time, immersive metaverse that connects hardware and software, from the edge to the cloud with rich data from Siemens\u2019 software and solutions.\u201d\""
  },
  {
    "question": "What is the name of the 3D artist featured in the article?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDgvMjkvamFuaWNlLWpvdXJuYWwtY2FudmFzLWJsZW5kZXItdGlrdG9rLWNhcGN1dC8=.pdf",
    "ground_truth_answer": "Janice.Journal",
    "ground_truth_context": "\"\nAdvantage AI: Elevated Creative Workflows in NVIDIA Canvas, Blender, TikTok and CapCut 3D Artist Janice.Journal creates the \u2018Eighth Wonder of the World\u2019 with AI-powered creativity this week \u2018In the NVIDIA Studio.\u2019\n\nAuthor: Gerardo Delgado\n\nEditor\u2019s note: This post is part of our weekly In the NVIDIA Studio series, which celebrates featured artists, offers creative tips and tricks and demonstrates how NVIDIA Studio technology improves creative workflows. We\u2019re also deep-diving on new GeForce RTX 40 Series GPU features, technologies and resources and how they dramatically accelerate content creation.\n\nAs beautiful and extraordinary as art forms can be, it can be easy to forget the simple joy and comforting escapism that content creation can provide for artists across creative fields.\n\nJanice K. Lee, a.k.a Janice.Journal \u2014 the subject of this week\u2019s In the NVIDIA Studio installment \u2014 is a TikTok sensation using AI to accelerate her creative process, find inspiration and automate repetitive tasks.\n\nAlso this week, NVIDIA Studio technology is powering some of the most popular mobile and desktop apps \u2014 driving creative workflows of both aspiring artists and creative professionals.\n\nWeek by week, AI becomes more ubiquitous within content creation.\n\nTake the popular social media app TikTok. All of its mobile app features, including AI Green Screen, are accelerated by GeForce RTX GPUs in the cloud. Other parts of TikTok creator workflows are also accelerated \u2014 Descript AI, a popular generative AI-powered video editing app, runs 50% faster on the latest NVIDIA L4 Tensor Core GPUs versus T4 Tensor Core GPUs .\n\nCapCut, the most widely used video editor by TikTok users, enables Simultaneous Scene Encoding, a functionality that sends independent groups of scenes to an NVIDIA Encoder (NVENC), contributing to shorter video export times without affecting image quality. This technology performs over 2x faster on NVIDIA GeForce RTX 4080 graphics cards versus on Apple\u2019s M2 Ultra.\n\nAdvanced users can move footage to their preferred desktop video editing app using native GPU-acceleration and RTX technology. This includes AV1 dual encoders ( NVIDIA GeForce RTX 4070 Ti graphics cards or higher required) for 40% better video quality for livestreamers, while video editors can slash export times nearly in half.\n\nJanice.Journal, a self-taught 3D creator, was motivated to learn new art skills as a way to cope with her busy schedule.\n\n\u201cI was going through a tough time during my junior year of college with classes and clubs,\u201d she said. \u201cWith no time to hang out with friends or decompress, my only source of comfort was learning something new every night for 20 minutes.\u201d\n\nHer passion for 3D creation quickly became evident. While Janice.Journal does consulting work during the day, she deep-dives into 3D creation at night, creating stunning scenes and tutorials to help other artists get started.\""
  },
  {
    "question": "What is the name of the new architecture used in the GeForce RTX 40 Series laptop GPUs?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDEvMDMvZ2FtaW5nLWNyZWF0b3Itcm9ib3RpY3MtYXV0by1jZXMv.pdf",
    "ground_truth_answer": "The new architecture used in the GeForce RTX 40 Series laptop GPUs is called the NVIDIA Ada Lovelace architecture.",
    "ground_truth_context": "\"\nNVIDIA Reveals Gaming, Creator, Robotics, Auto Innovations at CES New GeForce RTX GPUs, hyper-efficient laptops, new Omniverse capabilities among highlights of CES special address.\n\nAuthor: Brian Caulfield\n\nPowerful new GeForce RTX GPUs, a new generation of hyper-efficient laptops and new Omniverse capabilities and partnerships across the automotive industry were highlights of a news-packed address ahead of this week\u2019s CES trade show in Las Vegas.\n\n\u201cAI will define the future of computing and this has influenced much of what we\u2019re covering today,\u201d said Jeff Fisher, senior vice president for gaming products at NVIDIA, as he kicked off the presentation.\n\nFisher was joined by several leaders from NVIDIA to introduce products and partnerships across gaming and content creation, robotics and next-generation automobiles.\n\nThe headline news:\n\nGeForce RTX 40 Series laptops deliver company\u2019s largest-ever generational leap in performance and power efficiency to 170+ laptops for gamers and designers.\n\nGeForce RTX 40 Series Studio laptops will bring new power and efficiency to creators, gamers and designers .\n\nNVIDIA launches GeForce RTX 4070 Ti graphics cards, faster than RTX 3090 Ti, bringing power and efficiency of NVIDIA Ada architecture to $799.\n\nDLSS 3 comes to 50 released and upcoming games .\n\nNVIDIA bringing RTX 4080 performance to GeForce NOW cloud-gaming service .\n\nHyundai Motor Group, BYD and Polestar adopt GeForce NOW for cars .\n\nFoxconn partners with NVIDIA to build automated electric vehicles and manufacture NVIDIA DRIVE Orin computers for the global automotive market .\n\nMercedes-Benz to use NVIDIA Omniverse to assemble next-generation factories in \u201cdigital-first\u201d approach.\n\nMajor updates to NVIDIA Omniverse Enterprise enhance performance and offer new deployment options.\n\nNVIDIA opens Omniverse portals with generative AIs for 3D and RTX Remix; releases AI avatar builder Omniverse ACE in early access .\n\nNVIDIA Isaac Sim gets next-gen simulation tools for robotics development .\n\nFisher said the performance and power efficiency of the NVIDIA GeForce RTX 40 Series Laptop GPUs enable the greatest ever generational leap, including 14-inch gaming and creating powerhouse laptops, starting at $999 in February.\n\nNew GeForce RTX 4070 Ti graphics cards for desktops are faster than last generation\u2019s RTX 3090 Ti at nearly half the power, bringing the NVIDIA Ada Lovelace architecture down to $799, with availability starting Jan. 5.\n\nAnd DLSS 3 is being adopted by developers faster than any prior NVIDIA tech, with 50 released and upcoming titles, including Witchfire , The Day Before , Warhaven , THRONE AND LIBERTY and Atomic Heart .\n\nIn addition, RTX 4080 performance is coming to the NVIDIA GeForce NOW cloud-gaming service. As a result, Fisher said millions more gamers will have access to the NVIDIA Ada architecture with GeForce NOW\u2019s Ultimate membership.\""
  },
  {
    "question": "What is Project Helix?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDUvMjgvY29tcHV0ZXgtZ2VuZXJhdGl2ZS1haS1ydHgv.pdf",
    "ground_truth_answer": "Project Helix is a collaboration between NVIDIA and Dell to make it easier for enterprises to build and deploy trustworthy generative AI on premises.",
    "ground_truth_context": "\"\n\u201cOur recent work with NVIDIA on Project Helix centers on making it easier for enterprises to build and deploy trustworthy generative AI on premises. Another step in this historic moment is bringing generative AI to PCs. Think of app developers looking to perfect neural network algorithms while keeping training data and IP under local control. This is what our powerful and scalable Precision workstations with NVIDIA RTX GPUs are designed to do. And as the global leader in workstations, Dell is uniquely positioned to help users securely accelerate AI applications from the edge to the datacenter.\u201d \u2014 Ed Ward, president of the client product group at Dell Technologies\n\n\u201cThe generative AI era is upon us, requiring immense processing and fully optimized hardware and software. With the NVIDIA AI platform, including NVIDIA Omniverse, which is now preinstalled on many of our products, we are excited to see the AI revolution continue to take shape on ASUS and ROG laptops.\u201d \u2014 Galip Fu, director of global consumer marketing at ASUS\n\nSoon, laptops and mobile workstations with RTX GPUs will get the best of both worlds. AI inference-only workloads will be optimized for Tensor Core performance while keeping power consumption of the GPU as low as possible, extending battery life and maintaining a cool, quiet system. The GPU can then dynamically scale up for maximum AI performance when the workload demands it.\n\nDevelopers can also learn how to optimize their applications end-to-end to take full advantage of GPU-acceleration via the NVIDIA AI for accelerating applications developer site .\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/05/28/computex-generative-ai-rtx/\""
  },
  {
    "question": "What is the name of the simulation technology used by READY Robotics to program robot tasks?",
    "document": "TGVhZGluZyBFbGVjdHJvbmljcyBNYW51ZmFjdHVyZXJzIDUvMjgvMjMucGRm.pdf",
    "ground_truth_answer": "The simulation technology used by READY Robotics to program robot tasks is called Isaac Sim.",
    "ground_truth_context": "\"\nAnd at the application level, Isaac Sim allows companies to build and optimally deploy AI-based robots. Manufacturers can work with industrial automation company READY Robotics to program their robot tasks in simulation before deploying in the real world. Simulation technology partners like SoftServe and FS Studio shorten development timelines for customers by building digital twin-based simulations.\n\nAlso at the application level, NVIDIA Metropolis includes a collection of factory-automation AI workflows that enable industrial solution providers and manufacturers to develop, deploy and manage customized quality-control solutions that save cost and improve production throughput. A large partner ecosystem \u2014 including ADLINK, Aetina, Deloitte, Quantiphi and Siemens \u2014 is helping to bring these solutions to market.\n\nLearn more about Omniverse, Isaac Sim and Metropolis at COMPUTEX.\n\nAbout NVIDIA Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company\u2019s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the industrial metaverse. NVIDIA is now a full-stack computing company with data- center-scale offerings that are reshaping industry. More information at https://nvidianews.nvidia.com/\""
  },
  {
    "question": "What is the name of the blog post that discusses the best games to play on RTX 40 series GPUs?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDQvMjEvZ2Vmb3JjZS1ydHgtMzAtNDAtc2VyaWVzLw==.pdf",
    "ground_truth_answer": "The name of the blog post is 'The Best Games to Play on RTX 40 Series GPUs'.",
    "ground_truth_context": "\"\nThe Best Games to Play on RTX 40 Series GPUs\n\nHow to Stream Like a Pro with an RTX 40 Series GPU\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/04/21/geforce-rtx-30-40-series/\""
  },
  {
    "question": "How did Runway, a New York-based startup, benefit from implementing CV-CUDA?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDMvMjEvY3YtY3VkYS1haS1jb21wdXRlci12aXNpb24v.pdf",
    "ground_truth_answer": "Runway implemented CV-CUDA and achieved a 3.6x speedup in preprocessing high-resolution videos, enabling real-time, click-to-content responses across its suite of creation tools.",
    "ground_truth_context": "\"\nThe Shenzhen-based multimedia conglomerate has achieved a 20% reduction in energy and cost for image processing over their previous GPU-optimized pipelines.\n\nAnd Beijing-based search giant Baidu is integrating CV-CUDA into FastDeploy , one of the open-source deployment toolkits of the PaddlePaddle Deep Learning Framework , which enables seamless computer vision acceleration to developers in the open-source community.\n\nApplications for CV-CUDA are growing. More than 500 companies have reached out with over 100 use cases in just the first few months of the alpha release.\n\nIn content creation and e-commerce, images use pre- and post-processing operators to help recommender engines recognize, locate and curate content.\n\nIn mapping, video ingested from mapping survey vehicles requires preprocessing and post-processing operators to train neural networks in the cloud to identify infrastructure and road features.\n\nIn infrastructure applications for self-driving simulation and validation software , CV-CUDA enables GPU acceleration for algorithms that are already occurring in the vehicle, such as color conversion, distortion correction, convolution and bilateral filtering.\n\nLooking to the future, generative AI is transforming the world of video content creation and curation, allowing creators to reach a global audience.\n\nNew York-based startup Runway has integrated CV-CUDA, alleviating a critical bottleneck in preprocessing high-resolution videos in their video object segmentation model.\n\nImplementing CV-CUDA led to a 3.6x speedup, enabling Runway to optimize real-time, click-to-content responses across its suite of creation tools.\n\n\u201cFor creators, every second it takes to bring an idea to life counts,\u201d said Crist\u00f3bal Valenzuela, co-founder and CEO of Runway. \u201cThe difference CV-CUDA makes is incredibly meaningful for the millions of creators using our tools.\u201d\n\nTo access CV-CUDA, visit the CV-CUDA GitHub .\n\nOr learn more by checking out the GTC sessions featuring CV-CUDA. Registration is free .\n\nOvercoming Pre- and Post-Processing Bottlenecks in AI-Based Imaging and Computer Vision Pipelines [S51182] ,\n\nBuilding AI-Based HD Maps for Autonomous Vehicles [SE50001] ,\n\nConnect With the Experts: GPU-Accelerated Data Processing with NVIDIA Libraries [CWES52014] ,\n\nAdvancing AI Applications with Custom GPU-Powered Plugins for NVIDIA DeepStream [S51612] .\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/03/21/cv-cuda-ai-computer-vision/\""
  },
  {
    "question": "What is the name of the partnership between Siemens and NVIDIA?",
    "document": "U2llbWVucyBOVklESUEgNi8yOS8yMi5wZGY=.pdf",
    "ground_truth_answer": "The partnership between Siemens and NVIDIA is called Siemens Xcelerator.",
    "ground_truth_context": "\"\n\u201cSiemens and NVIDIA share a common vision that the industrial metaverse will drive digital transformation. This is just the first step in our joint effort to make this vision real for our customers and all parts of the global manufacturing industry,\u201d said Jensen Huang, founder and CEO, NVIDIA. \u201cThe connection to Siemens Xcelerator will open NVIDIA\u2019s Omniverse and AI ecosystem to a whole new world of industrial automation that is built using Siemens\u2019 mechanical, electrical, software, IoT and edge solutions.\u201d\n\nThis partnership brings together complementary technologies and ecosystems to realize the industrial metaverse. Siemens is uniquely positioned at the intersections of the real and digital world, information technology and operational technology. The Siemens Xcelerator platform connects mechanical, electrical and software domains across the product and production processes and enables the convergence of IT and OT.\n\nNVIDIA Omniverse is an AI-enabled, physically simulated and industrial-scale virtual-world engine that enables for the first time full-fidelity live digital twins. NVIDIA AI, used by more than 25,000 companies worldwide, is the world\u2019s most popular AI platform and the intelligence engine of Omniverse in the cloud and autonomous systems at the edge. NVIDIA Omniverse and AI are ideal computation engines to represent the comprehensive digital twin from Siemens Xcelerator.\n\nAbout NVIDIA Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company\u2019s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics and ignited the era of modern AI. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry. More information at https://nvidianews.nvidia.com/.\n\nSiemens AG (Berlin and Munich) is a technology company focused on industry, infrastructure, transport, and healthcare. From more resource-efficient factories, resilient supply chains, and smarter buildings and grids, to cleaner and more comfortable transportation as well as advanced healthcare, the company creates technology with purpose adding real value for customers. By combining the real and the digital worlds, Siemens empowers its customers to transform their industries and markets, helping them to transform the everyday for billions of people. Siemens also owns a majority stake in the publicly listed company Siemens Healthineers, a globally leading medical technology provider shaping the future of healthcare. In addition, Siemens holds a minority stake in Siemens Energy, a global leader in the transmission and generation of electrical power.\n\nIn fiscal 2021, which ended on September 30, 2021, the Siemens Group generated revenue of \u20ac62.3 billion and net income of \u20ac6.7 billion. As of September 30, 2021, the company had around 303,000 employees worldwide. Further information is available on the Internet at www.siemens.com.\""
  },
  {
    "question": "Which highly anticipated game is launching on May 2 with DLSS 3?",
    "document": "TmV1cmFsIEdyYXBoaWNzIERMU1MgMyAzLzE2LzIzLnBkZg==.pdf",
    "ground_truth_answer": "Redfall, Bethesda's highly anticipated, open-world, co-op first-person shooter from Arkane Austin, is launching on May 2 with DLSS 3.",
    "ground_truth_context": "\"\nNVIDIA Accelerates Neural Graphics PC Gaming Revolution at GDC With New DLSS 3 PC Games and Tools\n\nAI-Powered NVIDIA DLSS 3 Comes to New AAA Games Including Diablo IV; DLSS Frame Generation Publicly Available for Developers at GDC\n\nAhead of next week\u2019s Game Developers Conference (GDC), NVIDIA announced an expanded game roster and new developer plug-ins for NVIDIA DLSS 3.\n\nThe latest version of NVIDIA\u2019s AI-powered Deep Learning Super Sampling (DLSS) technology is now supported in an assortment of blockbuster games and franchises, and being integrated into Unreal Engine, one of the world\u2019s most popular game engines. The company is also publicly releasing the DLSS Frame Generation plug-in to further ease developer adoption of the technology.\n\n\u201cNeural graphics has revolutionized gaming since its introduction with NVIDIA DLSS, and we\u2019re now taking it to new heights,\u201d said Matt Wuebbling, vice president of global GeForce marketing at NVIDIA. \u201cPC gaming super-franchises such as Diablo and Forza Horizon and Bethesda\u2019s new Redfall are raising the bar for image quality with stunning graphics while using DLSS to keep gameplay smooth as silk.\u201d\n\nSince its launch in 2018, NVIDIA DLSS has driven a neural graphics revolution in PC gaming. Neural graphics intertwines AI and graphics to create an accelerated rendering pipeline that continuously learns and improves. Instead of natively rendering every pixel in a frame, DLSS allows the game to render 1/8th of the pixels then uses AI and GeForce RTX\u2122 Tensor Cores to reconstruct the rest of the pixels, dramatically multiplying frame rates, while delivering crisp, high-quality images that rival native resolution.\n\nDiablo IV, Forza Horizon 5, Redfall \u2014 DLSS 3 is in the Biggest Games and Biggest Franchises To date, over 270 games and applications use NVIDIA DLSS as an AI-powered performance accelerator. DLSS 3, the latest version of the technology, is available in 28 released games and has been adopted 7x faster than DLSS 2 in the first six months of their respective launches.\n\nAmong the highly anticipated games being added to the DLSS roster is Forza Horizon 5, named the best open-world racing game of all time by several media outlets and currently holding the highest rating of any racing game tracked by OpenCritic. Forza Horizon 5, which already supports ray tracing, will update to DLSS 3 on March 28.\n\nRedfall, Bethesda\u2019s highly anticipated, open-world, co-op first-person shooter from Arkane Austin, the award-winning team behind Prey and Dishonored, is launching on May 2 with DLSS 3.\n\nIn addition, Diablo IV, the latest installment of the genre-defining Diablo franchise \u2014 multiple games of which are considered among the best of all time \u2014 will be launching on June 6 with DLSS 3.\""
  },
  {
    "question": "What is the name of the NVIDIA cloud service provider partners that host the DGX Cloud infrastructure?",
    "document": "TlZJRElBIEh1Z2dpbmcgRmFjZSA4LzgvMjMucGRm.pdf",
    "ground_truth_answer": "Leading NVIDIA cloud service provider partners.",
    "ground_truth_context": "\"\nDGX Cloud Speeds Development and Customization for Massive Models Each instance of DGX Cloud features eight NVIDIA H100 or A100 80GB Tensor Core GPUs for a total of 640GB of GPU memory per node. NVIDIA Networking provides a high-performance, low-latency fabric that ensures workloads can scale across clusters of interconnected systems to meet the performance requirements of advanced AI workloads.\n\nSupport from NVIDIA experts is included with DGX Cloud to help customers optimize their models and quickly resolve development challenges.\n\nDGX Cloud infrastructure is hosted by leading NVIDIA cloud service provider partners.\n\nAvailability The NVIDIA DGX Cloud integration with Hugging Face is expected to be available in the coming months.\n\nWatch Huang\u2019s SIGGRAPH keynote address on demand to learn more about NVIDIA DGX Cloud.\n\nAbout Hugging Face Hugging Face is the collaboration platform for the machine learning community.\n\nThe Hugging Face Hub works as a central place where anyone can share, explore, discover, and experiment with open- source ML. HF empowers the next generation of machine learning engineers, scientists and end users to learn, collaborate and share their work to build an open and ethical AI future together.\n\nWith the fast-growing community, some of the most used open-source ML libraries and tools, and a talented science team exploring the edge of tech, Hugging Face is at the heart of the AI revolution.\n\nAbout NVIDIA Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company\u2019s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling industrial digitalization across markets. NVIDIA is now a full-stack computing company with data- center-scale offerings that are reshaping industry. More information at https://nvidianews.nvidia.com/.\""
  },
  {
    "question": "What is the focus of GTC 2022?",
    "document": "R1RDIDIwMjIgMi8xNC8yMi5wZGY=.pdf",
    "ground_truth_answer": "Accelerated computing, deep learning, data science, digital twins, networking, quantum computing, and computing in the data center, cloud and edge, with a focus on how AI can help visualize and further climate science.",
    "ground_truth_context": "\"\nNVIDIA GTC 2022 to Feature Keynote From CEO Jensen Huang, New Products, 900+ Sessions From Industry and AI Leaders\n\nTop Technologists from Deloitte, Epic Games, Mercedes-Benz, Microsoft, Pfizer, Sony, Visa, Walt Disney, Zoom and More to Present\n\nNVIDIA today announced that it will host its GTC 2022 conference virtually from March 21-24, with a news-filled keynote by its founder and CEO Jensen Huang and more than 900 sessions from 1,400 speakers, including some of the world\u2019s top researchers and industry leaders in AI, high performance computing and graphics.\n\nRegistration is free and open now at www.nvidia.com/gtc.\n\nHuang\u2019s keynote will be live-streamed on Tuesday, March 22, at 8 a.m. Pacific time and available on demand afterward. Registration is not required to view the keynote.\n\n\u201cAs one of the world\u2019s leading AI conferences, GTC provides a singular opportunity to help solve huge challenges and redefine the future for developers, researchers and decision-makers across industries, academia, business and government,\u201d said Greg Estes, vice president of Developer Programs at NVIDIA. \u201cThere\u2019s a mother lode of content and opportunities for attendees of all levels to deepen their knowledge and make new connections.\u201d\n\nThis GTC will focus on accelerated computing, deep learning, data science, digital twins, networking, quantum computing and computing in the data center, cloud and edge. There will be more than 20 dedicated sessions on how AI can help visualize and further climate science.\n\nAmong the many notable speakers at GTC:\n\nAndrew Ng, founder of DeepLearning.AI, founder and CEO of Landing AI Prof. Dr. Bjorn Stevens, managing director and director of the department, The Atmosphere in the Earth System, Max Planck Institute for Meteorology Prof. Chelsea Finn, assistant professor of computer science, Stanford University Hao Yang, vice president of AI Research, Visa Jack Jin, lead machine learning Infra engineer, Zoom Joe Ucuzoglu, CEO, Deloitte U.S. Lidia Fonseca, chief digital and technology officer, Pfizer Magnus \u00d6stberg, chief software officer, Mercedes-Benz AG Marc Petit, general manager for Unreal Engine, Epic Games Markus Gross, vice president of Research, Walt Disney Studios Michael Russinovich, CTO and Technical Fellow, Microsoft Azure Natalya Tatarchuk, director of global graphics, Unity Peter Stone, executive director, Sony AI, and professor of computer science, University of Texas, Austin Dr. Stefan Sicklinger, head of BigLoop and Advanced Systems, CARIAD/VW Group Yu Liu, director of AI, Meta Zoe Lofgren, member of Congress, U.S. House of Representatives\n\nOther organizations participating include Amazon, Autodesk, Barclays, Bloomberg, Cisco, Cornell University, DeepMind, Dell Technologies, Ericsson, Flipkart, Google Brain, Lockheed Martin, NASA, NFL, Snap, U.S. Air Force and VMware.\""
  },
  {
    "question": "Who is Zoe Jewell and what is her role in wildlife conservation?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDgvMjIvYWktZHJvbmUtcmhpbm8tcG9hY2hlcnMv.pdf",
    "ground_truth_answer": "Zoe Jewell is a wildlife biologist and the co-founder of WildTrack, a global network of biologists and conservationists dedicated to non-invasive wildlife monitoring techniques. She has a B.Sc. in Zoology/Physiology, an M.Sc in Medical Parasitology from the London School of Tropical Medicine and Hygiene and a veterinary medical degree from Cambridge University. She has long sought to find less invasive ways to track, and protect, endangered species, such as the African black rhino.",
    "ground_truth_context": "\"\nAn AI-Enabled Drone Could Soon Become Every Rhino Poacher\u2019s\u2026 Horn Enemy\n\nAuthor: Brian Caulfield\n\nWant inspiration? Try being charged by a two-ton African black rhino.\n\nEarly in her career, wildlife biologist Zoe Jewell and her team came across a mother rhino and her calf and carefully moved closer to get a better look.\n\nThe protective mother rhino charged, chasing Jewell across the dusty savannah. Eventually, Jewell got a flimsy thorn bush between herself and the rhino. Her heart was racing.\n\n\u201cI thought to myself, \u2018There has to be a better way,\u2019\u201d she said.\n\nIn the latest example of how researchers like Jewell are using the latest technologies to track animals less invasively, a team of researchers has proposed harnessing high-flying AI-equipped drones powered by the NVIDIA Jetson edge AI platform to track the endangered black rhino through the wilds of Namibia.\n\nIn a paper published this month in the journal PeerJ , the researchers show the potential of drone-based AI to identify animals in even the remotest areas and provide real-time updates on their status from the air.\n\nFor more, read the full paper at https://peerj.com/articles/13779/ .\n\nWhile drones \u2014 and technology of just about every kind \u2014 have been harnessed to track African wildlife, the proposal promises to help gamekeepers move faster to protect rhinos and other megafauna from poachers.\n\n\u201cWe have to be able to stay one step ahead,\u201d said Jewell, co-founder of WildTrack , a global network of biologists and conservationists dedicated to non-invasive wildlife monitoring techniques.\n\nJewell, president and co-founder of WildTrack, has a B.Sc. in Zoology/Physiology, an M.Sc in Medical Parasitology from the London School of Tropical Medicine and Hygiene and a veterinary medical degree from Cambridge University. She has long sought to find less invasive ways to track, and protect, endangered species, such as the African black rhino.\n\nIn addition to Jewell, the paper\u2019s authors include conservation biology and data science specialists at UC Berkeley, the University of G\u00f6ttingen in Germany, Namibia\u2019s Kuzikus Wildlife Reserve and Duke University.\n\nThe stakes are high.\n\nAfrican megafauna have become icons, even as global biodiversity declines.\n\n\u201cOnly 5,500 black rhinos stand between this magnificent species, which preceded humans on earth by millions of years, and extinction,\u201d Jewell says.\n\nThat\u2019s made them bigger targets for poachers, who sell rhino horns and elephant tusks for huge sums, the paper\u2019s authors report. Rhino horns, for example, reportedly go for as much as $65,000 per kilogram.\n\nTo disrupt poaching, wildlife managers must deploy effective protection measures.\n\nThis, in turn, depends on getting reliable data fast.\n\nThe challenge: many current monitoring technologies are invasive, expensive or impractical.\n\nSatellite monitoring is a potential tool for the biggest animals \u2014 such as elephants. But detecting smaller species requires higher resolution imaging.\""
  },
  {
    "question": "How can AI help government bodies work within budget constraints?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDcvMTMvZ2VuZXJhdGl2ZS1haS1mb3ItaW5kdXN0cmllcy8=.pdf",
    "ground_truth_answer": "AI can help government bodies work within budget constraints by processing documents to speed the delivery of vital services, such as those provided by Medicare, Medicaid, Veterans Affairs, USPS, and the State Department.",
    "ground_truth_context": "\"\nThe analytical capabilities of AI can also help process documents to speed the delivery of vital services provided by organizations like Medicare, Medicaid, Veterans Affairs, USPS and the State Department.\n\nGenerative AI could be a pivotal tool to help government bodies work within budget constraints, deliver government services more quickly and achieve positive public sentiment.\n\nAcross every field, organizations are transforming employee productivity, improving products and delivering higher-quality services with generative AI.\n\nTo put generative AI into practice, businesses need expansive amounts of data, deep AI expertise and sufficient compute power to deploy and maintain models quickly. Enterprises can fast-track adoption with the NeMo generative AI framework, part of NVIDIA AI Enterprise software, running on DGX Cloud . NVIDIA\u2019s pretrained foundation models offer a simplified approach to building and running customized generative AI solutions for unique business use cases.\n\nLearn more about powerful generative AI tools to help your business increase productivity, automate tasks, and unlock new opportunities for employees and customers.\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/07/13/generative-ai-for-industries/\""
  },
  {
    "question": "How can generative AI improve productivity in the energy industry?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDcvMTMvZ2VuZXJhdGl2ZS1haS1mb3ItaW5kdXN0cmllcy8=.pdf",
    "ground_truth_answer": "Generative AI can improve productivity in the energy industry by reducing the need for manual research and analysis, and by providing instant answers to highly technical questions through AI chatbots. This can save employees up to 1.8 hours per day searching for information, which is nearly 20% of the work week.",
    "ground_truth_context": "\"\nIn the energy industry , AI is powering predictive maintenance and asset optimization, smart grid management, renewable energy forecasting, grid security and more.\n\nTo meet growing data needs across aging infrastructure and new government compliance regulations, energy operators are looking to generative AI.\n\nIn the U.S., electric utility companies spend billions of dollars every year to inspect, maintain and upgrade power generation and transmission infrastructure.\n\nUntil recently, using vision AI to support inspection required algorithms to be trained on thousands of manually collected and tagged photos of grid assets, with training data constantly updated for new components. Now, generative AI can do the heavy lifting.\n\nWith a small set of image training data, algorithms can generate thousands of physically accurate images to train computer vision models that help field technicians identify grid equipment corrosion, breakage, obstructions and even detect wildfires . This type of proactive maintenance enhances grid reliability and resiliency by reducing downtime, while diminishing the need to dispatch teams to the field.\n\nGenerative AI can also reduce the need for manual research and analysis. According to McKinsey, employees spend up to 1.8 hours per day searching for information \u2014 nearly 20% of the work week. To increase productivity, energy companies can train LLMs on proprietary data, including meeting notes, SAP records, emails, field best practices and public data such as standard material data sheets.\n\nWith this type of knowledge repository connected to an AI chatbot, engineers and data scientists can get instant answers to highly technical questions. For example, a maintenance engineer troubleshooting pitch control issues on a turbine\u2019s hydraulic system could ask a bot: \u201cHow should I adjust the hydraulic pressure or flow to rectify pitch control issues on a model turbine from company X?\u201d A properly trained model would deliver specific instructions to the user, who wouldn\u2019t have to look through a bulky manual to find answers.\n\nWith AI applications for new system design, customer service and automation, expect generative AI to enhance safety and energy efficiency, as well as reduce operational expenses in the energy industry.\n\nFrom intelligent tutoring systems to automated essay grading, AI has been employed in education for decades. As universities use AI to improve teacher and student experiences, they\u2019re increasingly dedicating resources to build AI-focused research initiatives.\""
  },
  {
    "question": "What is the name of the architecture that the NVIDIA L40S GPU is based on?",
    "document": "TlZJRElBLCBHbG9iYWwgRGF0YSBDZW50ZXIgU3lzdGVtIDgvOC8yMy5wZGY=.pdf",
    "ground_truth_answer": "The NVIDIA L40S GPU is based on the NVIDIA Ada Lovelace GPU architecture.",
    "ground_truth_context": "\"\nNVIDIA, Global Data Center System Manufacturers to Supercharge Generative AI and Industrial Digitalization\n\nOVX Servers Feature New NVIDIA GPUs to Accelerate Training and Inference, Graphics- Intensive Workloads; Coming Soon From Dell Technologies, Hewlett Packard Enterprise, Lenovo, Supermicro and More\n\nSIGGRAPH\u2014NVIDIA today announced NVIDIA OVX\u2122 servers featuring the new NVIDIA\u00ae L40S GPU, a powerful, universal data center processor designed to accelerate the most compute-intensive, complex applications, including AI training and inference, 3D design and visualization, video processing and industrial digitalization with the NVIDIA Omniverse\u2122 platform.\n\nThe new GPU powers accelerated computing workloads for generative AI, which is transforming workflows and services across industries, including text, image and video generation, chatbots, game development, product design and healthcare.\n\n\u201cAs generative AI transforms every industry, enterprises are increasingly seeking large-scale compute resources in the data center,\u201d said Bob Pette, vice president of professional visualization at NVIDIA. \u201cOVX systems with NVIDIA L40S GPUs accelerate AI, graphics and video processing workloads, and meet the demanding performance requirements of an ever- increasing set of complex and diverse applications.\u201d\n\nPowerful Performance for AI and Graphics NVIDIA OVX systems will enable up to eight NVIDIA L40S GPUs per server, each equipped with 48GB of memory. Based on the NVIDIA Ada Lovelace GPU architecture, the L40S includes fourth-generation Tensor Cores and an FP8 Transformer Engine, delivering over 1.45 petaflops of tensor processing power. For complex AI workloads with billions of parameters and multiple data modalities \u2014 such as text and video \u2014 L40S enables up to 1.2x more generative AI inference performance and up to 1.7x training performance compared with the NVIDIA A100 Tensor Core GPU.\n\nTo power high-fidelity professional visualization workflows like real-time rendering, product design and 3D content creation, the NVIDIA L40S GPU includes 142 third-generation RT Cores that deliver 212 teraflops of ray-tracing performance. This enables creative professionals to create immersive visual experiences and photorealistic content.\n\nFor computationally demanding workflows, such as engineering and scientific simulations, the NVIDIA L40S includes 18,176 CUDA\u00ae cores, delivering nearly 5x the single-precision floating-point (FP32) performance of the NVIDIA A100 GPU to accelerate complex calculations and data-intensive analyses.\n\nEarly Adoption Among the first cloud service providers to offer L40S instances is CoreWeave, which specializes in large-scale, GPU- accelerated workloads.\""
  },
  {
    "question": "What is the name of the software framework and cloud service developed by NVIDIA for generating, predicting, and understanding biomolecular data?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTAvMTAvbGxtcy1haS1ob3Jpem9uLw==.pdf",
    "ground_truth_answer": "NVIDIA BioNeMo.",
    "ground_truth_context": "\"\nGPT-3 helped motivate Stanford to create a center Liang now leads, exploring the implications of what it calls foundational models that can handle a wide variety of tasks well.\n\nLast year, NVIDIA announced the Megatron 530B LLM that can be trained for new domains and languages. It debuted with tools and services for training language models with trillions of parameters.\n\n\u201cLarge language models have proven to be flexible and capable \u2026 able to answer deep domain questions without specialized training or supervision,\u201d Bryan Catanzaro, vice president of applied deep learning research at NVIDIA, said at that time.\n\nMaking it even easier for users to adopt the powerful models, the NVIDIA Nemo LLM service debuted in September at GTC. It\u2019s an NVIDIA-managed cloud service to adapt pretrained LLMs to perform specific tasks.\n\nThe advances LLMs are making with proteins and chemical structures are also being applied to DNA.\n\nResearchers aim to scale their work with NVIDIA BioNeMo , a software framework and cloud service to generate, predict and understand biomolecular data. Part of the NVIDIA Clara Discovery collection of frameworks, applications and AI models for drug discovery, it supports work in widely used protein, DNA and chemistry data formats.\n\nNVIDIA BioNeMo features multiple pretrained AI models , including the MegaMolBART model, developed by NVIDIA and AstraZeneca.\n\nTransformers are also reshaping computer vision as powerful LLMs replace traditional convolutional AI models. For example, researchers at Meta AI and Dartmouth designed TimeSformer , an AI model that uses transformers to analyze video with state-of-the-art results.\n\nExperts predict such models could spawn all sorts of new applications in computational photography, education and interactive experiences for mobile users.\n\nIn related work earlier this year, two companies released powerful AI models to generate images from text.\n\nOpenAI announced DALL-E 2 , a transformer model with 3.5 billion parameters designed to create realistic images from text descriptions. And recently, Stability AI, based in London, launched Stability Diffusion ,\n\nLLMs also help developers write software. Tabnine \u2014 a member of NVIDIA Inception , a program that nurtures cutting-edge startups \u2014 claims it\u2019s automating up to 30% of the code generated by a million developers.\n\nTaking the next step, researchers are using transformer-based models to teach robots used in manufacturing, construction, autonomous driving and personal assistants.\n\nFor example, DeepMind developed Gato , an LLM that taught a robotic arm how to stack blocks. The 1.2-billion parameter model was trained on more than 600 distinct tasks so it could be useful in a variety of modes and environments, whether playing games or animating chatbots.\n\n\u201cBy scaling up and iterating on this same basic approach, we can build a useful general-purpose agent,\u201d researchers said in a paper posted in May.\""
  },
  {
    "question": "What will the AI lab and demonstration center be used for?",
    "document": "S3JvZ2VyIGFuZCBOVklESUEgMy8yMi8yMi5wZGY=.pdf",
    "ground_truth_answer": "The AI lab and demonstration center will be used to expand Kroger's freshness initiatives, improve shipping logistics, and create a better shopping experience in stores through digital twin simulations.",
    "ground_truth_context": "\"\nKroger and NVIDIA to Reinvent the Shopping Experience Through State-of-the-Art, AI-Enabled Applications and Services\n\nStrategic Collaboration to Advance Key Kroger Freshness Initiatives From Farm to Plate\n\nThe Kroger Co. (NYSE: KR) and NVIDIA today announced a strategic collaboration to reimagine the shopping experience using AI-enabled applications and services.\n\nKroger, the nation\u2019s largest grocer, and NVIDIA will build a state-of-art AI lab and demonstration center to expand Kroger\u2019s freshness initiatives, improve shipping logistics and create a better shopping experience in stores through digital twin simulations \u2014 virtual models designed to accurately reflect store layouts and other operations.\n\n\u201cOur collaboration with NVIDIA supports Kroger\u2019s \u2018Fresh for Everyone\u2019 commitment,\u201d said Wesley Rhodes, vice president of Technology Transformation & Research and Development at Kroger. \u201cWe look forward to learning more about how AI and data analytics will further our journey to provide our customers with anything, anytime, anywhere.\u201d\n\nThe lab will be located in Kroger\u2019s Cincinnati-based headquarters office. It will use the NVIDIA AI Enterprise software suite for retail, NVIDIA Omniverse\u2122 Enterprise to build digital twin simulations and NVIDIA cuOpt to explore logistics optimizations. The initial installation will use nine NVIDIA DGX\u2122 A100 systems, NVIDIA InfiniBand networking and NVIDIA RTX\u2122 workstations to gather actionable insights on the grocer\u2019s nearly 2,800 stores across the United States.\n\n\u201cNVIDIA and Kroger\u2019s collaboration on AI and digital twins will further expand Kroger\u2019s digital technology leadership,\u201d said Azita Martin, vice president and general manager of Retail at NVIDIA. \u201cKroger already is delivering excellent customer experiences in stores and providing fast home delivery. With NVIDIA AI, shoppers gain more personalized experiences in physical stores and online.\u201d\n\nThe companies will explore how NVIDIA technology can:\n\nIdentify early indicators of deteriorating freshness through computer vision and analytics. Use dynamic routing for last-mile delivery to ensure freshness from farm to plate Optimize store efficiency and processes with digital twin store simulation\n\nLearn more about Kroger\u2019s AI journey in the NVIDIA GTC AI Implementers Panel. To learn more about NVIDIA AI software, watch the GTC 2022 keynote from NVIDIA CEO Jensen Huang, and register for GTC for free to attend sessions with NVIDIA and industry leaders.\n\nAbout Kroger At The Kroger Co. (NYSE: KR), we are Fresh for Everyone\u2122 and dedicated to our Purpose: To Feed the Human Spirit\u00ae. We are, across our family of companies, nearly half a million associates who serve over 11 million customers daily through a seamless shopping experience under a variety of banner names. We are committed to creating #ZeroHungerZeroWaste communities by 2025. To learn more about us, visit our newsroom and investor relations site.\""
  },
  {
    "question": "What is the name of the ray-traced reimagining of Valve's classic game that will be streaming on GeForce NOW?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMDkvMjIvZ2Vmb3JjZS1ub3ctdGh1cnNkYXktc2VwdGVtYmVyLTIyLw==.pdf",
    "ground_truth_answer": "Portal with RTX is the ray-traced reimagining of Valve's classic game that will be streaming on GeForce NOW.",
    "ground_truth_context": "\"\nGo Hands On: Logitech G CLOUD Launches With Support for GeForce NOW\n\nPlus, \u2018Portal with RTX\u2019 and more to join GeForce NOW this fall, and eight new games including the \u2018Total War\u2019 series streaming this week.\n\nAuthor: GeForce NOW Community\n\nWhen it rains, it pours. And this GFN Thursday brings a downpour of news for GeForce NOW members.\n\nThe Logitech G CLOUD is the latest gaming handheld device to support GeForce NOW, giving members a brand new way to keep the gaming going.\n\nBut that\u2019s not all: Portal with RTX joins GeForce NOW in November, free for Portal owners. Find out more about this ray-traced reimagining of Valve\u2019s classic game, and more titles like A Plague Tale: Requiem and Warhammer 40,000: Darktide , streaming this fall.\n\nPlus, conquer a breathtaking fantasy world and engage in colossal real-time battles as Creative Assembly\u2019s Total Warhammer series comes to GeForce NOW \u2014 included in the eight new titles joining the GeForce NOW library this week.\n\nFinally, an update to the GeForce NOW app on PC and Mac begins rolling out this week with optimized streaming resolution support for 16:10 4K displays at up to 60 frames per second, perfect for RTX 3080 members streaming on Macbooks.\n\nThe just-announced G CLOUD is the latest way to stream your PC library from the cloud on GeForce NOW.\n\nDeveloped in partnership with Tencent Games, the G CLOUD is an Android device with a seven-inch 1080p 16:9 touchscreen, fully customizable controls and support for GeForce NOW right out of the box.\n\nMembers can instantly stream GeForce NOW\u2019s library of 1,000+ games that support gamepad, using touch controls or G CLOUD\u2019s built-in, customizable precision gaming controls. Its lightweight design makes it a joy to hold during the most frantic action. And thanks to its 12+ hour battery life, the action can last all day.\n\nThe G CLOUD is available to preorder today at $299.99 for a limited time, with full availability in October for $349.99. Check out the device .\n\nGet ready to play three new release titles coming to the cloud in the near future.\n\nPortal with RTX releases in November as free downloadable content for all Portal owners, and will be streaming on GeForce NOW. It\u2019s a ray-traced reimagining of Valve\u2019s classic game, built using a revolutionary modding tool called NVIDIA RTX Remix .\n\nIn Portal with RTX , full ray tracing transforms each scene, enabling light to bounce and be affected by each area\u2019s new high-resolution, physically based textures and enhanced high-poly models. Every light is ray traced and casts shadows, global illumination indirect lighting naturally illuminates and darkens rooms, volumetric ray-traced lighting scatters through fog and smoke, and shadows are pixel perfect.\n\nWishlist the Portal with RTX DLC on Steam now to be notified the second it\u2019s released.\n\nA tale continues when A Plague Tale: Requiem launches Tuesday, Oct. 18, enhanced with ray-traced effects.\""
  },
  {
    "question": "What is the name of the framework provided by NVIDIA for building high-performing recommender systems at scale?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTIvMDcvYWktZW50ZXJwcmlzZS1zb2Z0d2FyZS0zLw==.pdf",
    "ground_truth_answer": "NVIDIA Merlin",
    "ground_truth_context": "\"\nNVIDIA Clara Parabricks and MONAI improve healthcare: New support for NVIDIA Clara Parabricks enables faster, more accurate genomic analysis for sequencing centers, clinical labs, genomics researchers and genomics instrument manufacturers. NVIDIA AI Enterprise also supports MONAI , a domain-specific medical imaging AI framework that provides pretrained models and a collaborative, scalable workflow for data labeling and training robust AI models.\n\nNVIDIA AI frameworks to boost customer service, safety, sales and more: The 50+ frameworks and pretrained models now supported in NVIDIA AI Enterprise 3.0 include NVIDIA Riva , a GPU-accelerated speech AI software development kit for building and deploying fully customizable, real-time AI pipelines that deliver world-class accuracy in all leading clouds, on premises, at the edge and on embedded devices. NVIDIA Morpheus enables cybersecurity developers to create optimized AI pipelines for filtering, processing and classifying large volumes of real-time data. SDKs in the NVIDIA Metropolis intelligent video analytics platform, such as TAO Toolkit and NVIDIA DeepStream for vision AI, are supported, as is the NVIDIA Merlin open-source framework for building high-performing recommender systems at scale.\n\nExpanded certification for the cloud: With NVIDIA AI Enterprise 3.0, organizations with a hybrid cloud strategy now have the flexibility to run the software on GPU-accelerated instances from Oracle Cloud Infrastructure . Customers who purchase a license through one of NVIDIA\u2019s channel partners can deploy in OCI with full certification and support from NVIDIA on designated OCI instances. This is in addition to existing NVIDIA AI Enterprise certification for accelerated instances on Amazon Web Services, Google Cloud and Microsoft Azure.\n\nHewlett Packard Enterprise and NVIDIA extend AI support for hybrid data centers : HPE and NVIDIA will deliver a joint offering that provides support for the NVIDIA AI Enterprise 3.0 on HPE GreenLake and HPE Ezmeral. The solution allows customers to speed up AI application development, securely, by easily procuring and deploying NVIDIA AI Enterprise on a managed HPE GreenLake instance.\n\nBroadened storage and virtualization support : NVIDIA AI Enterprise 3.0 now supports NVIDIA Magnum IO GPUDirect Storage , which provides a direct data path between local or remote storage and GPU memory to further speed AI workloads. It also delivers expanded virtualization options, including Red Hat Enterprise Linux with KVM and VMware vSphere 8 .\n\nNVIDIA AI Enterprise is available now. Customers can contact NVIDIA partners worldwide for pricing. NVIDIA AI Enterprise 3.0 is expected to be available for customers with current and new subscriptions later this month. A license for NVIDIA AI Enterprise is also included with servers from NVIDIA partners that feature NVIDIA H100 PCIe GPUs, including systems from Dell Technologies, Hewlett Packard Enterprise, Lenovo and Supermicro.\""
  },
  {
    "question": "What is the name of the artist who created the VFX shots in the example?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjIvMTIvMDcvaW4tdGhlLW52aWRpYS1zdHVkaW8tZGVjZW1iZXItMDcv.pdf",
    "ground_truth_answer": "The artist's name is Lippman.",
    "ground_truth_context": "\"\nThe majority of Make Your VFX Shots Look REAL was built in DaVinci Resolve\u2019s Fusion page, featuring a node-based workflow with hundreds of 2D and 3D tools. He uploaded footage from his Blackmagic Pocket Cinema Camera in 6K resolution then proceeded to composite VFX.\n\nThe artist started by refining motion blur, a key element of any movement in camera footage shot in 24 frames per second or higher. Animated elements like the blue fireball must include motion blur, or they\u2019ll look out of place. Applying a transform node with motion blur, done faster with a GeForce RTX GPU, created the necessary realism, Lippman said.\n\nLippman then lit the scene and enhanced elements in the composition by emitting absent light in the original footage. He creates lighting and adds hues by using a probe modifier on the popular DaVinci Resolve color corrector, a GPU-accelerated task.\n\nThe artist then matches movement, critical for adding 2D or 3D effects to footage. In this case, Lippman replaced the straightforward blue sky with a haunting, cloudy, gloomy gray. Within Fusion, Lippman selected the merge mode, connecting the sky with the composition. He then right clicked the center of the video and used the Merge:1 Center , Modify With and Tracker position features with minor adjustments to complete tracking movement.\n\nLippman rounds out his creative workflow with color matching. He said it\u2019s critical to have the proper mental approach alongside realistic expectations while applying VFX composition.\n\n\u201cOur goal is not to make our VFX shots look real, it\u2019s to make them look like they were shot on the same camera, on the same lens, at the same time of the original footage,\u201d said Lippman. \u201cA big part of it is matching colors, contrast and overall brightness with all of the scene elements.\u201d\n\nLippman color matched the sky, clouds and UFO by adding a color-corrector node to a single cloud node, tweaking the hue and likeness to match the rest of the sky. Edits were then applied to the remaining clouds. Lippman also applied a color-correction node to the UFO, tying up the scene with matching colors.\n\nWhen it came time for final exports, the exclusive NVIDIA dual encoders found in GeForce RTX 40 Series GPUs slashed Lippman\u2019s export time by half. This can help freelancers like him meet sharp deadlines. The dual encoders can be found in Adobe Premiere Pro (via the popular Voukoder plug-in), Jianying Pro (China\u2019s top video-editing app) and DaVinci Resolve.\n\n\u201cThe GeForce RTX 4080 is a powerhouse and definitely gives you the ability to do more with less,\u201d he said. \u201cIt\u2019s definitely faster than the dual RTX 2080 GPU setup I\u2019d been using and twice as fast as the RTX 3080 Ti, while using less power and costing around the same. Plus, it unlocks the AV1 Codec in DaVinci Resolve and streaming in AV1.\u201d\n\nCheck out his review .\""
  },
  {
    "question": "What is the name of Sweden's first astronaut?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDEvMjQvYWktc3dlZGVuLWJlcnplbGl1cy8=.pdf",
    "ground_truth_answer": "Christer Fuglesang",
    "ground_truth_context": "\"\nOthers will use Berzelius to improve detection of cancer cells and navigate the massive mounds of data in human genomes.\n\nSome researchers are exploring tools such as NVIDIA Omniverse Avatar Cloud Engine and NVIDIA BotMaker to create animated patients. Powered by GPT-SW3, they could help doctors practice telemedicine skills.\n\nSweden\u2019s work in image and video recognition will get a boost from Berzelius. Such algorithms advance work on the autonomous systems used in modern factories and warehouses.\n\nOne project is exploring how autonomous systems act in space and undersea. It\u2019s a topic close to the heart of a recent addition to WASP, researcher Christer Fuglesang, who was named Sweden\u2019s first astronaut in 1992.\n\nFuglesang went to the International Space Station in 2006 and 2008. Later, as a professor of physics at Sweden\u2019s Royal Institute of Technology, he collaborated with Ynnerman on live shows about life in space, presented in the WISDOME dome theater at the Visualization Center C Ynnerman founded and directs.\n\nThanks to his expertise in visualization, \u201cI can go to Mars whenever I want,\u201d Ynnerman quipped.\n\nHe took NVIDIA founder and CEO Jensen Huang and Marcus Wallenberg \u2014 scion of Sweden\u2019s leading industrial family \u2014 on a tour of outer space at the dome to mark the Berzelius upgrade. The dome can show the Martian surface in 8K resolution at 120 frames per second, thanks to its use of 12 NVIDIA Quadro RTX 8000 GPUs .\n\nYnnerman\u2019s algorithms have touched millions who\u2019ve seen visualizations of Egyptian mummies at the British Museum.\n\n\u201cThat makes me even more proud than some of my research papers because many are young people we can inspire with a love for science and technology,\u201d he said.\n\nA passion for science and technology has attracted more than 400 active Ph.D. candidates so far to WASP, which is on the way to exceeding its goal of 600 grads by 2031.\n\nBut even a visualization specialist can\u2019t be everywhere. So Ynnerman\u2019s pet project will use AI to create a vibrant, virtual museum guide.\n\n\u201cI think we can provide more people a \u2018wow\u2019 experience \u2014 I want a copilot when I\u2019m navigating the universe,\u201d he said.\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/01/24/ai-sweden-berzelius/\""
  },
  {
    "question": "What is the impact of stock-based compensation expense, acquisition-related costs, and other costs on NVIDIA's GAAP operating expenses?",
    "document": "RmluYW5jaWFsIFJlc3VsdHMgUTJGWTI0IDgvMjMvMjMucGRm.pdf",
    "ground_truth_answer": "$315 million",
    "ground_truth_context": "\"\n211 $\n\n184 $\n\n159 $\n\n394 $\n\n315\n\n(C) Other consists of assets held for sale related adjustments.\n\n(D) Income tax impact of non-GAAP adjustments, including the recognition of excess tax benefits or deficiencies related to stock-based compensation under GAAP accounting standard (ASU 2016-09).\n\nNVIDIA CORPORATION RECONCILIATION OF GAAP TO NON-GAAP OUTLOOK\n\nQ3 FY2024\n\nOutlook\n\n($ in millions)\n\nGAAP gross margin\n\nImpact of stock-based compensation expense, acquisition-related costs, and other costs\n\nNon-GAAP gross margin\n\nGAAP operating expenses\n\n$\n\nStock-based compensation expense, acquisition-related costs, and other costs\n\nNon-GAAP operating expenses\n\n$\n\nAbout NVIDIA Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company\u2019s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling industrial digitalization across markets. NVIDIA is now a full-stack computing company with data- center-scale offerings that are reshaping industry. More information at https://nvidianews.nvidia.com/.\""
  },
  {
    "question": "What is the name of the latest vehicle revealed by XPENG?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDcvMDUveHBlbmctZzYtY291cGUtc3V2LWRyaXZlLW9yaW4v.pdf",
    "ground_truth_answer": "The latest vehicle revealed by XPENG is the G6.",
    "ground_truth_context": "\"\nBased on the more than 35,000 preorders reported for the G6 after its reveal at Auto Shanghai earlier this year, drivers are eager to get moving in this latest offering from XPENG\u2019s software-defined fleet.\n\nOriginal URL: https://blogs.nvidia.com/blog/2023/07/05/xpeng-g6-coupe-suv-drive-orin/\""
  },
  {
    "question": "What is the name of the upcoming NVIDIA product that is expected to be in full production and available to enterprises worldwide soon?",
    "document": "SG9wcGVyIEdQVSBFeHBhbnNpb24gMy8yMS8yMy5wZGY=.pdf",
    "ground_truth_answer": "The name of the upcoming NVIDIA product that is expected to be in full production and available to enterprises worldwide soon is DGX H100 AI supercomputer.",
    "ground_truth_context": "\"\nCertain statements in this press release including, but not limited to, statements as to: the benefits, impact, performance, features and availability of our products, collaborations, partnerships and technologies, including Hopper GPUs, H100 Tensor Core GPUs, DGX H100, A100, NVLink high-speed interconnects, Quantum InfiniBand, Spectrum Ethernet, NVIDIA AI software stack, NVIDIA AI Enterprise, NVIDIA Base Command, and the DGX platform including DGX Cloud; NVIDIA DGX H100 AI supercomputers being in full production and coming soon to enterprises worldwide; innovators worldwide receiving the first wave of DGX H100; and Mitsui building the world\u2019s first generative AI supercomputer for drug discovery are forward- looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing product and technologies; market acceptance of our products or our partners products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the companys website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward- looking statements to reflect future events or circumstances.\n\n\u00a9 2023 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, DGX, NVIDIA Base Command, NVIDIA Hopper, NVIDIA Spectrum and NVLink are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability and specifications are subject to change without notice.\n\nAllie Courtney NVIDIA Corporation +1-408-706-8995 acourtney@nvidia.com\""
  },
  {
    "question": "What is the name of the platform that NVIDIA is working on for industrial and medical environments?",
    "document": "SUdYIEVkZ2UgQUkgOS8yMC8yMi5wZGY=.pdf",
    "ground_truth_answer": "The platform is called IGX.",
    "ground_truth_context": "\"\nFor management of IGX in industrial and medical environments, NVIDIA Fleet Command\u2122 allows organizations to deploy secure, over-the-air software and system updates from a central cloud console.\n\nBuilding the Industrial Edge NVIDIA is working with a broad ecosystem of companies to bring the IGX platform to market.\n\nOne of the first companies to use IGX at the edge is Siemens, a technology leader in industrial automation and digitalization, which is working with NVIDIA on a vision for autonomous factories.\n\nSiemens is collaborating with NVIDIA to expand its work across industrial computing, including with digital twins and for the industrial metaverse.\n\nThe collaboration will allow enterprises to complement work carried out using the NVIDIA Omniverse\u2122 platform for 3D design and collaboration and the Siemens Xcelerator open digital business platform with the powers of IGX. The platform enables data generated from digital twins in the virtual world to be used to train intelligent machines operating in real-life factories and warehouses using industrial-grade computing infrastructure from Siemens.\n\nSiemens is already adding next-level perception into its edge-based applications through NVIDIA Metropolis. With millions of sensors in factories, Metropolis connects entire fleets of robots and IoT devices to bring AI into industrial environments, making it one of the key application frameworks for edge AI running on top of the IGX platform.\n\n\u201cAs part of our ongoing collaboration with NVIDIA to speed digital transformation, Siemens will bring IGX technologies to our industrial compute portfolio to help reduce repetitive tasks in the factory and better support workers,\u201d said Rainer Brehm,\n\nCEO of factory automation at Siemens. \u201cBy more closely connecting smart devices on the factory floor and using that data for intelligent machine operation in production, we can increase efficiency and flexibility for our customers.\u201d\n\nMade for Medical Environments For healthcare, the IGX platform supports NVIDIA Clara\u2122 Holoscan \u2014 a real-time, AI computing platform for medical devices \u2014 enabling the rapid development and production deployment of new devices that deliver AI applications directly into operating rooms, where over 300 million surgeries are delivered each year globally.\n\nMore than 70 medical-device companies, startups and medical centers have already been using Holoscan to advance their efforts in deploying AI applications to clinical settings and evolving medical devices to a software-as-a-service business model. Among them are Activ Surgical, Moon Surgical and Proximie, which are building next-generation surgical systems. With Clara Holoscan and IGX, Moon Surgical said it saved significant engineering time in its imaging pipelines, management system and hardware while developing its next-generation Maestro surgical robot assistant.\""
  },
  {
    "question": "What are some of the advanced features of NVIDIA Maxine?",
    "document": "YmxvZ3MubnZpZGlhLmNvbS9ibG9nLzIwMjMvMDgvMDgvbWF4aW5lLTNkLXZpZGVvLWNvbW11bmljYXRpb25zLw==.pdf",
    "ground_truth_answer": "Some of the advanced features of NVIDIA Maxine include Background Noise Removal, Super Resolution, Eye Contact, Interpreter, Voice Font, and Audio Super Resolution.",
    "ground_truth_context": "\"\nExtended Cut: NVIDIA Expands Maxine for Video Editing, Showcases 3D Virtual Conferencing Research Production version of Maxine now available in NVIDIA AI Enterprise; research demo presents how 3D technology can enhance video communications.\n\nAuthor: Rick Champagne\n\nProfessionals, teams, creators and others can tap into the power of AI to create high-quality audio and video effects \u2014 even using standard microphones and webcams \u2014 with the help of NVIDIA Maxine .\n\nThe suite of GPU-accelerated software development kits and cloud-native microservices lets users deploy AI features that enhance audio, video and augmented-reality effects for real-time communications services and platforms. Maxine will also expand features for video editing, enabling teams to reach new heights in video communication.\n\nPlus, an NVIDIA Research demo at this week\u2019s SIGGRAPH conference displays how AI can take video conferencing to the next level with 3D features.\n\nWireless connectivity has enabled people to join virtual meetings from more locations than ever. Typically, audio and video quality are heavily impacted when a caller is on the move or in a location with poor connectivity.\n\nAdvanced, real-time Maxine features \u2014 such as Background Noise Removal, Super Resolution and Eye Contact \u2014 allow remote users to enhance interpersonal communication experiences.\n\nIn addition, Maxine can now be used for video editing. NVIDIA partners are transforming this professional workflow with the same Maxine features that elevate video conferencing. The goal when editing a video, whether a sales pitch or a webinar, is to engage the broadest audience possible. Using Maxine, professionals can tap into AI features that enhance audio and video signals.\n\nWith Maxine, a spokesperson can look away from the screen to reference notes or a script while their gaze remains as if looking directly into the camera. Users can also film videos in low resolution and enhance the quality later. Plus, Maxine lets people record videos in several different languages and export the video in English.\n\nMaxine features to be released in early access this year include:\n\nInterpreter: Translates from simplified Chinese, Russian, French, German and Spanish to English while animating the user\u2019s image to show them speaking English.\n\nVoice Font: Enables users to apply characteristics of a speaker\u2019s voice and map it to the audio output.\n\nAudio Super Resolution : Improves audio quality by increasing the temporal resolution of the audio signal and extending bandwidth. It currently supports upsampling from 8,000Hz to 16,000Hz as well as from 16,000Hz to 48,000Hz. This feature is also updated with more than 50% reduction in latency and up to 2x better throughput.\""
  }
]